2020簡介0619

Associate Research Fellow 王建民 研 究 Chien-Min Wang 人 員 Ph.D., Electrical Engineering, National Taiwan University, Taiwan Faculty T +886-2-2788-3799 ext. 1703 E [email protected] F +886-2-2782-4814 W wcmwwwa.inisg.sinica.edu.tw/pages/pages/ ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica (1991-1995) ・ Associate Research Fellow, Institute of Information Science, Academia Sinica (1996-present) Research Description My current research interests include cloud computing, services computing, and human-centered computing. For cloud computing, we aim at e cient and scalable processing of huge datasets. We proposed the design pattern called two-phase data processing to allow dependence within a set of input key-value pairs and enable MapReduce to exploit coarse-grained parallelism. We also proposed a solution for large-scale generalized su x array (GSA) construction with MapReduce and an in-memory data store. It can construct GSA with a 4-fold larger input on the same hardware system, indicating better scalability than the original method. For services computing, we focus on the modeling and forecasting of QoS and workload of cloud services. Currently, several research works are ongoing, including (1) a comprehensive survey of current time-aware QoS forecasting research; (2) a long-term collection and profound analysis of a large-scale time-aware dynamic QoS dataset; (3) an empirical study to cloud workload forecasting problem; and (4) an improved genetic programming (GP)-based QoS time series forecasting approach. For human-centered computing, we focus on intelligent context-aware services with wearable devices. A human centered computing system should have three abilities: understanding the context about the user, providing the service that makes the lives better, and interacting with human naturally through perception. We studied activity recognition technology and presented a personalized and real-time prototyping solution on smart glasses. We also studied gesture recognition technology and introduced a novel TV control simulation system that recognizes hand gestures and track hand joints. Based on the result of context recognition, context-aware services can then perform appropriate actions and provide the desired information to the users. 1. Yang Syu, Chien-Min Wang, and Yong-Yi Fanjiang, \"Modeling Publications Brochure 2020 and Forecasting of Time-aware Dynamic QoS Attributes for Cloud Services,\" IEEE Transactions on Network and Service 6. Jan-Jan Wu, Shu-Fan Shih, Hsiangkai Wang, Pangfeng Liu, Management, Vol. 16, No. 1, pp. 56-71, March 2019. and Chien-Min Wang, \"QoS-aware Replica Placement for Grid Computing,\" Concurrency and Computation: Practice and 2. Yang Syu and Chien-Min Wang, \"An Empirical Investigation Experience, pp. 193-213, Vol. 24, No. 3, March 2012. of Real-World QoS of Web Services,\" Proceeding of the 16th International Conference on Services Computing, Lecture Notes 7. Chien-Min Wang, Hsi-Min Chen, Chun-Chen Hsu, and Jonathan in Computer Science, pages 48-65, June 2019. Lee, \"Dynamic Resource Selection Heuristics for a Non-reserved Bidding-based Grid Environment,\" Future Generation Computer 3. Yueh Wu and Chien-Ming Wang, \"Applying Hand Gestures Systems, Vol. 26, No. 2, pp. 183-197, February 2010. Recognition and Joints Tracking to TV Controller with CNN and Convolutional Pose Machine,\" Proceeding of the 24th 8. Jan-Jan Wu, Yi-Fang Lin, Da-Wei Wang, and Chien-Min Wang, International Conference on Pattern Recognition,\" Beijing, China, \"Optimizing Server Placement for Parallel I/O in Switch-based August 2018. Clusters,\" Journal of Parallel and Distributed Computing, Vol. 69, No. 3, pp. 266-281, March 2009. 4. Hsiang-Huang Wu and Chien-Min Wang, \"Generalization of Large-Scale Data Processing in one MapReduce job for 9. Chien-Min Wang, Chun-Chen Hsu, Pangfeng Liu, Hsi-Min Chen, Coarse-Grained Parallelism,\" International Journal of Parallel and Jan-Jan Wu, \"Optimizing Server Placement in Hierarchical Programming, Vol. 45, No. 4, pp. 797-826, August 2017. Grid Environments,\" The Journal of Supercomputing, pp. 267- 282, Vol. 42, No. 3, December 2007. 5. Ding-Yong Hong, Jan-Jan Wu, Pen-Chung Yew, Wei-Chung Hsu, Chun-Chen Hsu, Pangfeng Liu, Chien-Min Wang, and Yeh-Ching 10. Yi-Fang Lin, Chien-Min Wang, and Jan-Jan Wu, \"Optimizing I/ Chung, \"Efficient and Retargetable Dynamic Binary Translation O Server Placement for Parallel I/O on Switch-Based Irregular on Multicores,\" IEEE Transactions on Parallel and Distributed Networks,\" The Journal of Supercomputing, pp. 201-217, Vol. 36, Systems, Vol. 25, No. 3, pp. 622-632, February 2014. No. 3, June 2006. 151

究研 人 Research Fellow 員 王柏堯 Bow-Yaw Wang Faculty Ph.D., Computer Science, University of Pennsylvania, United States T +886-2-2788-3799 ext. 1717 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/~bywang ・ Research Fellow, Institute of Information Science, Academia Sinica (2012-present) ・ Professor (Adjunct), National Taiwan University (2013-present) ・ Associate Research Fellow, Institute of Information Science, Academia Sinica (2008- 2012) ・ Associate Professor (Adjoint), National Taiwan University (2009-2012) ・ Invited Professor, INRIA, France (2009-2011) ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica (2003-2008) ・ Invited Associate Professor, Tsinghua University, China (2009-2010) ・ Assistant Professor (Adjoint), National Taiwan University (2004-2009) Research Description My research interests include computational logic, automata theory and formal veri cation, especially including model checking. Formal verification is a mathematical and logic method that checks properties about computer systems. Among several techniques in formal veri cation, I am most interested in model checking. Given a formal property and a system description, a model checker veri es whether the system description conforms to the property. The model checking problem, in general, is computationally di cult, and therefore I have been developing algorithms and heuristics to improve e ciency. In recent years, my research interests have focused an applying formal veri cation to practical cryptography. Modern cryptography such as Elliptic Curve Cryptography requires computation over large nite elds. Commodity computing devise, however, do not support arithmetic computation on 255-bit integers, for example. Hence, arithmetic over large nite eld needs to be implemented with 64- or 32-bit machine instructions. If such implementations are incorrect, any security guarantees of cryptosystems would be lost. It is therefore of utmost importance to formally verify cryptographic programs deployed in computing devices. Along with my colleagues, we have successfully veri ed several group and eld operations implemented in several security libraries. I have also worked in formal privacy analysis. Privacy has been one of the most concerned issues in data analyses. Using advanced computing devices and machine learning techniques, digital personal information is collected and analyzed constantly. The scandal of Facebook and Cambridge Analytica is perhaps one of the most vivid massive privacy intrusion known to us. Since all data analyses are performed by programs, I have been applying formal techniques to verifying privacy properties on models of data analysis programs. Speci cally, data analysis programs are formalized as randomized algorithms in the di erential privacy framework. I have developed veri cation theories for di erential privacy on probabilistic models. Publications grained Control on Distributed Data Analytic (poster). 39th International Conference on Software Engineering (ICSE 2017), 1. Yu-Fu Fu, Jiaxiang Liu, Xiaomu Shi, Ming-Hsien Tsai, Bow- Buenos Aires, Argentina. May 2017. Yaw Wang, and Bo-Yin Yang. Signed Cryptographic Program Verification with Typed Cryptoline. 26 th ACM SIGSAC 7. Yu-Fang Chen, Chih-Duo Hong, Ondrej Lengal, Shin-Cheng Mu, Conference on Computer and Communications Security (CCS Nishant Sinha,and Bow-Yaw Wang. An Executable Sequential 2019), London, UK. November 2019. Specification for Spark Aggregation. 5th International Conference on Networked Systems (NETYS 2017), Marrakech, Morocco. 2. Jiaxiang Liu, Xiaomu Shi, Ming-Hsien Tsai, Bow-Yaw Wang, and May 2017. Bo-Yin Yang. Verifying Arithmetic in Cryptographic C Programs. 34th IEEE/ACM International Conference on Automated Software 8. Fei He, Shu Mao, and Bow-Yaw Wang. Learning-based Assume- Engineering (ASE 2019), San Diego, USA. November 2019. Guarantee Regression Verification. 28th International Conference on Computer Aided Verification (CAV 2016), Toronto, Ontario, 3. Depeng Liu, Bow-Yaw Wang, and Lijun Zhang. Model Checking Canada. July 2016. Differentially Private Properties. 16th Asian Symposium on Programming Languages and Systems (APLAS 2018), 9. Yu-Fang Chen, Chiao Hsieh, Ondrej Lengal, Tsung-Ju Lii, Ming- Wellington, New Zealand. December 2018. Hsien Tsai, Bow-Yaw Wang, and Farn Wang. PAC Learning- Based Verification and Model Synthesis. 38th International 4. Andy Polyakov, Ming-Hsien Tsai, Bow-Yaw Wang, and Bo-Yin Conference on Software Engineering (ICSE 2016), Austin, USA. Yang. Verifying Arithmetic Assembly Programs in Cryptographic May 2016. Primitives (invited). 29th International Conference on Concurrency Theory (CONCUR 2018), Beijing, China. September 2018. 10. Fei He, Xiaowei Gao, Miaofei Wang, Bow-Yaw Wang, and Lijun Zhang. Learning Weighted Assumptions for Compositional 5. Ming-Hsien Tsai, Bow-Yaw Wang, and Bo-Yin Yang. Certified Verification of Markov Decision Processes. ACM Transactions Verification of Algebraic Properties on Low-Level Mathematical Software Engineering and Methodology (TOSEM). 25(3): 21:1- Constructs in Cryptographic Programs. ACM Conference on 21:39 (2016). Computer and Communications Security (CCS 2017), Dallas, USA. October 2017. 6. Chen Luo, Fei He, Dong Yan, Dan Zhang, Xin Zhou, and Bow- Yaw Wang. PSpec: A Formal Specification Language for Fine- 152

Research Fellow 王新民 研 究 Hsin-Min Wang 人 員 Ph.D., Electrical Engineering, National Taiwan University, Taiwan Faculty T +886-2-2788-3799 ext. 1714 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/whm ・ Research Fellow, IIS, Academia Sinica (2010-present) ・ Deputy Director, Academia Sinica Center for Digital Cultures, Academia Sinica (2013-present) ・ Professor (Joint Appointment), Department of Computer Science and Information Engineering, National Cheng Kung University (2014-present) ・ Deputy Director, IIS, Academia Sinica (2011-2018) ・ Associate Research Fellow, IIS, Academia Sinica (2002-2010) ・ Assistant Research Fellow, IIS, Academia Sinica (1996-2002) ・ President, Association for Computational Linguistics and Chinese Language Processing (2013-2015) ・ Editorial Board Member, IJCLCLP (2004-2016), JISE (2012-2016), APSIPA TSIP (2014-present), IEEE/ACM TASLP (2016-2020) Research Description My research interests are in spoken language processing, natural language processing, and multimedia information retrieval. The research goal is to develop methods for analyzing, extracting, recognizing, indexing, and retrieving information from audio data, with special emphasis on speech and music. In the eld of speech, the recent research topics include discriminative autoencoders for speech and speaker recognition, subspace-based models for phonotactic spoken language recognition, variational autoencoder-based voice conversion, audio- visual speech enhancement, automatic speech quality assessment, autoencoder-based paragraph embeddings for spoken document retrieval and summarization, and spoken question answering. We have implemented our own large vocabulary continuous speech recognition (LVCSR) systems for Mandarin and Minnan. A Hakka LVCSR system will also be developed in the future. In the music eld, my recent research has been focused mainly on acoustic-phonetic F0 modeling for vocal melody extraction, emotion-oriented pseudo song prediction and matching for automatic music video generation, cover song identi cation, automatic generation of set lists for concert videos, music transcription and source separation, automatic melody generation, and singing voice conversion. 1. Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang, and Shou-De Publications Brochure 2020 Lin, \"Cost-sensitive multi-label learning for audio tag annotation and retrieval,\" IEEE Trans. on Multimedia, 13(3), pp. 518-529, on Audio, Speech, and Language Processing, 24(11), pp. 1998 - June 2011. 2008, November 2016. 2. Hung-Yi Lo, Shou-De Lin, and Hsin-Min Wang, \"Generalized 7. Shih-Hung Liu, Kuan-Yu Chen, Yu-Lun Hsieh, Berlin Chen, k-labelsets ensemble for multi-label and cost-sensitive Hsin-Min Wang, Hsu-Chun Yen, and Wen-Lian Hsu, \"A position- classification,\" IEEE Trans. on Knowledge and Data Engineering, aware language modeling framework for extractive broadcast 26(7), pp. 1679-1691, July 2014. news speech summarization,\" ACM Transactions on Asian and Low-Resource Language Information Processing, 16(4), pp. 1-13, 3. Ju-Chiang Wang, Yi-Hsuan Yang, Hsin-Min Wang, and Shyh- Article 27, August 2017. Kang Jeng, \"Modeling the affective content of music with a Gaussian mixture model,\" IEEE Trans. on Affective Computing, 8. Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, and Hsin-Min 6(1), pp. 56 - 68, March 2015. Wang, \"An information distillation framework for extractive summarization,\" IEEE/ACM Transactions on Audio, Speech, and 4. Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang, Language Processing, 26(1), pp. 161-170, January 2018. Ea-Ee Jan, Wen-Lian Hsu, Hsin-Hsi Chen, \"Extractive broadcast news summarization leveraging recurrent neural network 9. Jen-Chun Lin, Wen-Li Wei, Tyng-Luh Liu, Yi-Hsuan Yang, language modeling techniques,\" IEEE/ACM Trans. on Audio, Hsin-Min Wang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao, Speech, and Language Processing, 23(8), pp. 1322-1334, August \"Coherent deep-net fusion to classify shots in concert videos,\" 2015. IEEE Transactions on Multimedia , 20(11), pp. 3123-3136, November 2018. 5. Yu-Ren Chien, Hsin-Min Wang, and Shyh-Kang Jeng, \"An acoustic-phonetic model of F0 likelihood for vocal melody 10. Wen-Chin Huang, Hao Luo, Hsin-Te Hwang, Chen-Chou Lo, extraction,\" IEEE/ACM Trans. on Audio, Speech, and Language Yu-Huai Peng, Yu Tsao, and Hsin-Min Wang, \"Unsupervised Processing, 23(9), pp. 1457-1468, September 2015. representation disentanglement using cross domain features and adversarial learning in variational autoencoder based 6. Yu-Ren Chien, Hsin-Min Wang, and Shyh-Kang Jeng, voice conversion,\" accepted to appear in IEEE Transactions on \"Alignment of lyrics with accompanied singing audio based on Emerging Topics in Computational Intelligence. acoustic-phonetic vowel likelihood modeling,\" IEEE/ACM Trans. 153

究研 人 Associate Research Fellow 員 古倫維 Lun-Wei Ku Faculty Ph.D., Computer Science and Information Engineering, National Taiwan Univeristy, Taiwan T +886-2-2788-3799 ext. 1808 E [email protected] F +886-2-2782-4814 W www.lunweiku.com/ ・ Assistant & Associate Research Fellow, Institute of Information Science, Academia Sinica (2012-present) ・ Assistant & Associate Professor, National Chiao Tung University (2017-present) ・ Secretary-General, Association for Computational Linguistics and Chinese Language Processing (2015-present) ・ Information O cer, ACL-SIGHAN (2016-present) ・ AFNLP Executive Committee Members-at-Large (MAL), (2016-2018) Research Description My research interests lie in subjective information processing, specifically sentiment analysis and opinion mining, which is a subarea of natural language processing (NLP), and its interplay with knowledge inference (AI) and computer human interaction (CHI). I am most interested in understanding how the subjective information such as emotions, opinions, lies, and sarcasm expressed or perceived by people, aroused by content, and inferred in events, especially through text media. In addition, I pay attention to the utilization of knowledge for better understanding and downstream applications. In the past, I have developed the well-known popular Chinese sentiment analysis tool CSentiPackage, which includes sentiment dictionaries, labeled resources, the scoring module, and the deep learning model. On top of these useful materials, my lab has developed technologies such as the state of the art stance classi cation model UTCNN, the emotion noti cation system for social media EmotionPush, the reading preference guided article recommendation system PGA, and the knowledge enriched visual storytelling model KG-Story. I organized previously NTCIR MOAT and currently EmotionX sentiment research challenges which attract researchers in my area to work on important topics together. Toward the goal of leveraging subjective information analysis techniques to improve the quality of life, I am working on several foundational topics in natural language understanding, such as semantic role labeling and sentence parsing, as well as many advanced topics including smart distance supervision, multi-modal content generation, lie detection, knowledge-based co-training, long inference, fake news intervention, and human-like agent construction. Publications 6. Chieh-Yang Huang, Mei-Hua Chen and Lun-Wei Ku, \"Towards a Better Learning of Near-Synonyms: Automatically Suggesting 1. Chao-Chun Hsu, Zi-Yuan Chen, Chi-Yang Hsu, Chih-Chia Li, Example Sentences via Filling in the Blank,\" In Proceedings of Tzu-Yuan Lin, Ting-Hao Huang, Lun-Wei Ku, \"Knowledge- the 26th International World Wide Web Conference (WWW 2017), Enriched Visual Storytelling,\" In Proceedings of the Thirty- Digital Learning Track. Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), February 7 - 12, 2020, New York, USA. 7. Wei-Chung Wang and Lun-Wei Ku, \"Enabling Transitivity for Lexical Inference on Chinese Verbs Using Probabilistic Soft 2. YunZhu Song, Hong-Han Shuai, Sung-Lin Yeh, Yi-Lun Wu, Lun- Logic,\" Proceedings of the 8th International Joint Conference on Wei Ku, Wen-Chih Peng, \"Attractive or Faithful? Popularity- Natural Language Processing (IJCNLP 2017), December 2017. Reinforced Learning for Inspired Headline Generation,\" In Proceedings of the Thirty-Fourth AAAI Conference on Artificial 8. Wei-Fan Chen and Lun-Wei Ku, \"UTCNN: a Deep Learning Intelligence (AAAI 2020) , February 7 - 12, 2020, New York, Model of Stance Classification on Social Media Text,\" The 26th USA. International Conference on Computational Linguistics (COLING 2016), December 2016. 3. Chia-Wei Chen, Sheng-Chuan Chou, Chang-You Tai and Lun-Wei Ku, \"PGA: Phrase-Guided Attention Web Article 9. Ku, Lun-Wei and Chen, Hsin-Hsi, \"Mining Opinions from the Recommendation for Next Clicks and Views,\" The IEEE/ACM Web: Beyond Relevance Retrieval,\" Journal of American Society International Conference on Social Networks Analysis and for Information Science and Technology, volume 58, number 12, Mining (ASONAM 2019), August 2019. pages 1838-1850, August 2007, Special Issue on Mining Web Resources for Enhancing Information Retrieval 4. Zi-Yuan Chen, Chih-Hung Chang, Yi-Pei Chen, Jijnasa Nayak and Lun-Wei Ku, \"UHop: An Unrestricted-Hop Relation 10. Ku, Lun-Wei, Liang, Yu-Ting and Chen, Hsin-Hsi, \"Opinion Extraction Framework for Knowledge-Based Question Extraction, Summarization and Tracking in News and Blog Answering,\" Proceedings of 2019 Annual Conference of the Corpora,\" Proceedings of AAAI-2006 Spring Symposium North American Chapter of the Association for Computational on Computational Approaches to Analyzing Weblogs, AAAI Linguistics (NAACL 2019), June 2019. Technical Report SS-06-03, pages 100-107, March 2006 5. Wei-Fan Chen and Lun-Wei Ku, \"We Like, We Post: A Joint User-Post Approach for Facebook Post Stance Labeling,\" IEEE Transactions on Knowledge and Data Engineering, volume 30, number 10, pages 2013-2023, October 2018. 154

Research Fellow 何建明 研 究 Jan-Ming Ho 人 員 Ph.D., Electrical Engineering and Computer Science, Faculty Northwestern University, United States T +886-2-2788-3799 ext. 1803 E [email protected] F +886-2-2782-4814 W ewinwdwe.xii.sh.stimnilca.edu.tw/pages/hoho/ ・ Deputy Executive Secretary, Board of Science & Technology, Executive Yuan, Taiwan (2019/6-present) ・ Member, Ministry of Education, higher Education Review Committee, Taiwan (2019/6-present) ・ Consultant（政務顧問）, Executive Yuan, Taiwan (2016/8-present) Research Description Jan-Ming Ho received his Ph.D. degree in Electrical Engineering and Computer Science from Northwestern University in 1989. He received his M.S. from the Institute of Electronics at National Chiao Tung University in 1980 and his B.S. in Electrical Engineering from National Cheng Kung University in 1978. Dr. Ho joined the Institute of Information Science, Academia Sinica, as an Associate Research Fellow in 1989, was promoted to Research Fellow in 1994, and from 2000 to 2003, he served as Deputy Director of the Institute. From 2004 to 2006, he served as Director General of the Division of Planning and Evaluation, National Science Council. He visited IBM’s T.J. Watson Research Center in the summers of 1987 and 1988, the Leonardo Fibonacci Institute for the Foundations of Computer Science, Italy, in the summer of 1992, and the Dagstuhl Seminar on Applied Combinatorial Methods in VLSI/CAD, Germany, in 1993. Dr. Ho’s current focus of research is designing efficient algorithms on combinatorial optimization with applications in de novo genome assembly and nancial computing. Dr. Ho has served as board member for several NGOs including the Institute of Information and Computing Machinery (IICM), the Taiwan Fintech Association, the Frontier Foundation, Taiwan, the Y.T. Lee Foundation on Science Education for All, and the WuSanLien Foundation on Taiwanese History. He also served as President of IICM from 2007 to 2009 and President of the Software Liberty Association Taiwan (SLAT) from 2004 to 2008. Publications 1. Jia-Hao Syu , Mu-En Wu , Shin-Huah Lee, and Jan-Ming Ho, 7. Yi-Cheng Tsai, Mu-En Wu, Jia-Hao Syu, Chin-Laung Lei, \"On the Design of Profitable Index Based on the Mechanism Chung-Shu Wu, Jan-Ming Ho, Chuan-Ju Wang,\" Assessing the of Random Trading,\" Proceedings, 12th Asian Conference on Profitability of Timely Opening Range Breakout on Index Futures Intelligent Information and Database Systems, ACIIDS 2020, Markets,\" IEEE Access, volume 7, April 2019. Springer, Phuket, Thailand, March 2020. 8. Li-An Yang, Yu-Jung Chang, Shu-Hwa Chen, Chung-Yen Lin 2. Sheng-Yao Su, I-Hsuan Lu, Wen-Chih Cheng, Wei-Chun Chung, and Jan-Ming Ho, \"SQUAT: A Sequencing Quality Assessment Pao-Yang Chen, Jan-Ming Ho, Shu-Hwa Chen, Chung-Yen Lin, Tool for Data Quality Assessments before and after Genome \"An Intuitive Web-based Framework for Genome-wide DNA Assemblies,\" BMC Genomics, volume 19, number Suppl 9, pages Methylation Analysis,\" to appear in BMC Genomics. 238, April 2019. 3. Jia-Hao Syu, Mu-En Wu, and Jan-Ming Ho, \"A Framework of 9. SH Chen, WY Kuo, SY Su, WC Chung, JM Ho, HHS Lu, CY Lin, Applying Kelly Stationary Index to Stock Trading in Taiwan \"A gene profiling deconvolution approach to estimating immune Market,\" IEEE Big Data, The 3rd International Workshop on Big cell composition from complex tissues,\" BMC Genomics, volume Data for Financial News and Data, IEEE, LA, USA, December 19, number Suppl 4, pages 154, May 2018. 2019. 10. Yi-Cheng Tsai, Chin-Laung Lei, William Cheung, Chung-Shu 4. Chen-Sheng Gu, Hong-Po Hsieh, Ray-I Chang and Jan-Ming Wu, Jan-Ming Ho, and Chuan-Ju Wang, \"Exploring the Persistent Ho, \"A Fund Selection Robo-Advisor with Deep-learning Driven Behavior of Financial Markets,\" Finance Research Letters, Market Prediction,\" IEEE SMC 2019, Oct. 6-9, 2019. volume 24, pages 199-220, March 2018. 5. Yun-Pin Tien, Wei-Chen Lin, Jan-Ming Ho and Wing-Kai Brochure 2020 Hon, \"Optimal File Dissemination Scheduling Under a General Binary Tree of Trust Relationship,\" TrustCom 2019 : The 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, August 2019. 6. Jia-Hao Syu, Mu-En Wu, Shin-Huah Lee, and Jan-Ming Ho, \"Modified ORB Strategies with Threshold Adjusting on Taiwan Futures Market,\" IEEE CIFEr 2019, May 4-5, 2019. 155

究研 人 Research Fellow 員 吳真貞 Jan-Jan Wu Faculty Ph.D., Computer Science, Yale University, United States T +886-2-2788-3799 ext. 1610 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/wuj ・ Research Fellow, Institute of Information Science, Academia Sinica (2011-present) ・ Associate Research Fellow, Institute of Information Science, Academia Sinica (2001- 2011) ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica (1996-2001) ・ Associate Software Engineer, Institute of Information Industry (1987-1989) ・ Ph.D., Computer Science, Yale University (1995) ・ M.S., Computer Science and Information Engineering, National Taiwan University (1987) ・ B.S., Computer Science and Information Engineering, National Taiwan University (1985) Research Description My research interests include resource management in parallel and cloud computing, parallel and distributed processing for big data, and dynamic binary translation for multicores/manycores. In resource management, we study dynamic provision, scheduling and management of virtual machines, automatic scaling of system resources for application service requirements, and dynamic resource management for performance/energy tradeo . In big data processing, we develop e cient data partitioning strategies for NoSQL databases, data caching and replacement techniques for in-memory cluster computing, and distributed algorithms for large- scale graph computing. In dynamic binary translation (DBT), we developed a system emulator, HQEMU, which supports e cient simulation of ARM binary execution on x86 architectures. We also extend our research to address important DBT issues in architectures with SIMD (single instruction, multiple data) extensions. Hardware manufacturers have adopted many distinct strategies for microprocessor design to improve parallelism, including multi-cores, many-cores, GPGPU, SIMD, and others. However, these parallel architectures have very di erent parallel execution models and thus substantial problems are encountered when migrating applications from one architecture to another: (1) application developers have to re-write programs based on the target execution model, which increases the time to market (2) legacy applications are poorly optimized due to under-utilization of parallelism in the target hardware, and thus, only a small fraction of the potential performance gain is realized. To overcome these problems, we developed an e cient and retargetable dynamic binary translator to transparently transform application binaries among di erent parallel execution models. In our current work, the DBT dynamically transforms binaries of short-SIMD loops to equivalent long-SIMD loops, in order to exploit the wider SIMD lanes of the hosts. Publications 7. Cing-Fu Jhu, Pangfeng Liu and Jan-Jan Wu, \"Data Pinning and Back Propagation Memory Optimization for Deep Learning on 1. Yu-Ping Liu, Ding-Yong Hong, Jan-Jan Wu, Sheng-Yu Fu, Wei- GPU,\" International Symposium on Computing and Networking, Chung Hsu, \"Exploiting SIMD Asymmetry in ARM-to-x86 Takayama, Japan, November 2018, (Outstanding Paper Award) Dynamic Binary Translation,\" ACM Transactions on Architecture and Code Optimization, volume 16, number 1, pages 2:1-2:24, 8. Li-Yung Ho, Jan-Jan Wu and Pangfeng Liu, \"Adaptive February 2019. Communication for Distributed Deep Learning on Commodity GPU Cluster,\" IEEE/ACM International Symposium on Cluster, 2. Ding-Yong Hong, Jan-Jan Wu, Yu-Ping Liu, Sheng-Yu Fu, Wei- Cloud and Grid Computing (CCGrid) , Washington DC, USA, Chung Hsu, \"Processor-Tracing Guided Region Formation in May 2018. Dynamic Binary Translation,\" ACM Transactions on Architecture and Code Optimization, volume 15, number 4, pages 52:1-52:25, 9. Olivier Valery, Pangfeng Liu, Jan-Jan Wu, \"Low precision November 2018. deep learning training on mobile heterogeneous platform,\" 26th Euromicro International Conference on Parallel, Distributed, and 3. Olivier Valery, Pangfeng Liu, Jan-Jan Wu, \"A collaborative Network-Based Processing (PDP 2018), Cambridge, UK, March CPU-GPU approach for deep learning on mobile devices,\" 2018. Concurrency and Computation: Practice and Experience, volume 31, number 17, pages published online, September 2019. 10. Sheng-Yu Fu, Chih-Min Lin, Ding-Yong Hong, Yu-Ping Liu, Jan- Jan Wu, Wei-Chung Hsu, \"Exploiting SIMD Capability in an 4. Ding-Yong Hong, Yu-Ping Liu, Sheng-Yu Fu, Jan-Jan Wu, Wei- ARMv7-to-ARMv8 Dynamic Binary Translator,\" International Chung Hsu, \"Improving SIMD Parallelism via Dynamic Binary Conference on Compilers, Architectures and Synthesis for Translation,\" ACM Transactions on Embedded Computing Embedded Systems (CASES), Turin, Italy, September 2018. Systems (TECS), volume 17, number 3, pages 61:1-61:27, February 2018. 11. Yu-Tung Hsieh, Chuan-Yu Lee, Ching-Chi Lin, Pangfeng Liu, and Jan-Jan Wu, \"A Bicameralism Voting Framework for 5. Olivier Valery, Pangfeng Liu, Jan-Jan Wu, \"A Collaborative CPU- Combining Knowledge from Clients into Better Prediction,\" GPU Approach for Principal Component Analysis on Mobile IEEE International Conference on Big Data, Los Angeles, CA, Heterogeneous Platform,\" Journal of Parallel and Distributed USA, December 2019. Computing (JPDC), volume 120, pages 44-61, October 2018. 6. Po-Yen Wu, Pangfeng Liu, and Jan-Jan Wu:, \"Versatile Communication Optimization for Deep Learning by Modularized Parameter Server,\" IEEE International Conference on Big Data , Seattle, USA, December 2018. 156

Research Fellow 呂及人 研 究 Chi-Jen Lu 人 員 Ph.D., Computer Science, University of Massachusetts at Amherst, United States Faculty T +886-2-2788-3799 ext. 1820 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/cjlu ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica (1999/8- 2003/10) ・ Associate Research Fellow, Institute of Information Science, Academia Sinica (2003/10- 2008/11) Research Description A common practice in machine learning is to learn a model (e.g. a classifier) in a batch way, in which one first collects a set of training examples and then learns a model from this training set. Afterwards, the learned model is used for all the future testing data, but it remains xed without being further updated. While this is su cient for many applications considered today, it may not work well for others. In fact, this does not seem to be the way we humans usually learn. This motivates the study of learning in the online setting, in which the learning process never stops as long as new data keeps coming. It has evolved into a fruitful research area of machine learning, and my works mainly cover the following two aspects. The rst is to identify existing learning algorithms which have been widely used but work in the batch setting, and transform them to work in the online setting. In this direction, we have successfully developed online versions of several powerful batch algorithms, such as boosting algorithms, principal components analysis, and tensor decomposition. The second aspect is on the topic known as the online decision problem, which captures the dilemma we often have to face: to make repeated decisions in unknown and changing environments and su er the consequences of our decisions. For this problem, we identi ed natural scenarios in which better online algorithms can be designed, and moreover, we extended the scope of the problem in several directions and develop new algorithms correspondingly. In addition, we also found new applications of the problem in the area of game theory. 1. Yi-Shan Wu, Po-An Wang, and Chi-Jen Lu, \"Lifelong Publications optimization with low regret,\" Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics 7. Chen-Yu Wei, Yi-Te Hong, and Chi-Jen Lu, \"Tracking the Best (AISTATS), April 2019. Expert in Non-stationary Stochastic Environments,\" Proceedings of the 30th Annual Conference on Neural Information Processing 2. Jun-Kun Wang, Chi-Jen Lu, and Shou-De Lin, \"Online linear Systems (NIPS), December 2016. optimization with sparsity constraints,\" Proceedings of the 30th International Conference on Algorithmic Learning Theory (ALT), 8. Po-An Chen and Chi-Jen Lu, \"Generalized mirror descents in March 2019. congestion games,\" Artificial Intelligence, volume 241, pages 217-243, December 2016. 3. Chi-Ning Chou, Kai-Min Chung and Chi-Jen Lu, \"On the Algorithmic Power of Spiking Neural Networks,\" The 10th 9. Chun-Liang Li, Hsuan-Tien Lin, and Chi-Jen Lu, \"Rivalry of Two Innovations in Theoretical Computer Science (ITCS 2019), Families of Algorithms for Memory-Restricted Streaming PCA,\" January 2019. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2016. 4. Jen-Hou Chou and Chi-Jen Lu, \"The communication complexity of graphical games on grid graphs,\" Proceedings of the 14th 10. Yi-Te Hong and Chi-Jen Lu, \"Online Learning in Markov Conference on Web and Internet Economics 14th Conference on Decision Processes with continuous actions,\" Proceedings of the Web and Internet Economics (WINE), December 2018. 26th International Conference on Algorithmic Learning Theory (ALT), Lecture Notes in Artificial Intelligence, October 2015. 5. C h e n - Yu We i , Yi - Te H o n g , a n d C h i - J e n L u , \" O n l i n e Reinforcement Learning in Stochastic Games,\" Proceedings of Brochure 2020 the 31st Annual Conference on Neural Information Processing Systems (NIPS), December 2017. 6. Po-An Wang and Chi-Jen Lu, \"Tensor Decomposition via Simultaneous Power Iteration,\" Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017. 157

究研 人 Research Fellow 員 呂俊賢 Chun-Shien Lu Faculty Ph.D., Electrical Engineering, National Cheng-Kung University, Taiwan T +886-2-2788-3799 ext. 1513 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/lcs ・ Research Fellow, Institute of Information Science, Academia Sinica (2013/3-present) ・ Deputy Director, Research Center for Information Technology Innovation, Academia Sinica (2015/4-2020/1) ・ Associate editor of IEEE Trans. on Image Processing (2010/12-2014) (2018/3-present) ・ Ta-You Wu Memorial Award, Ministry of Science and Technology, Taiwan, ROC (2007) Research Description My recent research interests are in the (Deep) Compressive Sensing and AI Security & Privacy. For compressive sensing (CS), it is a new paradigm of simultaneous sampling and compression. Without being restricted to the constraint of Nyquist rate, CS can, in theory, perfectly reconstruct the original signal under the constraints that only a few samples or measurements extracted from an original signal are needed and the signal is sparse. The unique characteristic of CS is that sampling and compression can be simultaneously achieved for use in resource-limited mobile devices. Nevertheless, there are several aspects needed to be considered in CS, including the design of sensing matrix and dictionary/basis, the sparsity or low-rank of signals, and time-consuming optimization for signal recovery. Thus, our motivation is to study the e cient and exible design of compressive sensing based on deep learning, called \"Deep Sensing.\" For arti cial intelligence (AI) security and privacy, due to the population and development of deep learning technologies, recent researches reveal that the sophisticated design of adversarial examples (inputs) can achieve efficient fooling effect on well-trained deep neural networks (DNNs). Meanwhile, the \"adversarial perturbations\" introduced by adversarial samples are indistinguishable from the benign inputs in terms of human perception. According to the literature, the amount of publications, pertaining to AI Security and Privacy, has been grown exponentially since 2014. This indicates that the issues of AI security and privacy has received much attention recently. In view of the observations regarding the relationship among AI Model, Security, Privacy, and Data Hiding, we study the issues of balancing model accuracy, AI security, and AI privacy. Publications 1. Yi-Lin Sung, Sung-Hsien Hsieh, Soo-Chang Pei, and Chun- 6. Chia-Mu Yu, Chun-Shien Lu, and Sy-Yen Kuo, \"Compressed Shien Lu, \"Difference-Seeking Generative Adversarial Network- Sensing-Based Clone Identification in Sensor Network,\" IEEE -Unseen Sample Generation,\" International Conference on Trans. on Wireless Communications , Vol. 15, No. 4, pp. 3071- Learning Representations (ICLR), Addis Ababa, Ethiopia, April 3084, 2016. 26-30, 2020. (full paper) 7. Yao-Tung Tsou, Chun-Shien Lu, and Sy-Yen Kuo, \"MoteSec- 2. Chia-Mu, Yu, Sarada Gochhayat, Mauro Conti, and Chun-Shien, Aware: A Practical Secure Mechanism for Wireless Sensor Lu, \"Privacy Aware Data Deduplication for Side Channel in Networks,\" IEEE Trans. on Wireless Communications, Vol. 12, Cloud Storage,\" Accepted and to Appear in IEEE Trans. on Cloud No. 6, pp. 2817-2829, 2013. Computing . 8. Chia-Mu Yu, Yao-Tung Tsou, Chun-Shien Lu, and Sy-Yen 3. Sung-Hsien Hsieh, Wei-Jie, Liang, Chun-Shien Lu, and Soo- Kuo, \"Localized Algorithms for Detection of Node Replication Chang Pei, \"Distributed Compressive Sensing: Performance Attacks in Mobile Sensor Networks,\" IEEE Trans. on Information Analysis with Diverse Signal Ensembles,'' Accepted and to Forensics, and Security, Vol. 8, No. 5, pp. 754-768, 2013. Appear in IEEE Trans. on Signal Processing. 9. Chao-Yung Hsu, Chun-Shien Lu, and Soo-Chang Pei, \"Image 4. Sung-Hsien Hsieh, Chun-Shien Lu, and Soo-Chang Pei, Feature Extraction in Encrypted Domain with Privacy-Preserving \"Compressive Sensing Matrix Design for Fast Encoding and SIFT,\" IEEE Trans. on Image Processing, Vol. 21, No. 11, pp. Decoding via Sparse Fourier Transform,\" IEEE Signal Processing 4593-4607, 2012. Letters, Vol. 25, No. 4, pp. 591-595, 2018. 10. Chun-Shien Lu and Chao-Yung Hsu, \"Constraint-Optimized 5. Wei-Jie, Liang, Gang-Xuan Lin, and Chun-Shien Lu, \"Tree Keypoint Removal/Insertion Attack: Security Threat to Scale- Structure Sparsity Pattern Guided Convex Optimization for Space Image Feature Extraction,\" ACM Multimedia Conference Compressive Sensing of Large-Scale Images,\" IEEE Trans. on (ACM MM), Oct. 30-Nov. 02, Nara, Japan, pp. 629-638, 2012. Image Processing, Vol. 26, No. 2, pp. 847-859, 2017. (full paper, acceptance rate 20.2%). 158

Research Fellow 宋定懿 研 究 Ting-Yi Sung 人 員 Ph.D., Operations Research, New York University, United States Faculty T +886-2-2788-3799 ext. 1711 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/tsung/ ・ Associate Research Fellow, Institute of Information Science, Academia Sinica (1989- 2000) ・ Deputy Director, Institute of Information Science, Academia Sinica (1996-1999) ・ Ten Outstanding Young Women Award (1998) Research Description My research interest is bioinformatics for proteomics and proteogenomics. Studying proteomics is crucial for biomedical research because proteins perform cellular functions and are also drug targets. Mass spectrometry (MS) has become a predominant technology for large-scale proteomics research in the past years. Thus we started to work on bioinformatics for MS-based proteomics in late 2003. When we investigated the challenges of identifying missing proteins which lack experiment evidence at the protein level, we observed a great portion of missing proteins with evidence at transcript level have sequence variants in their protein sequences. Furthermore, it is reported in the literature that single amino acid variations (SAVs) can lead to or are related to cancers; for example, the SAV L858R in the epidermal growth factor receptor has been observed at genomic level in lung cancer patients of Taiwan. However, most of variant peptides containing cancer-related SAVs have not been identi ed from MS experiments, i.e., not being detected at the protein level. Thus we are also interested in bioinformatics for proteogenomics to validate genetic variation events at the protein level. The main tasks of MS data analysis include protein identi cation and quantitation for proteomics studies and variant peptide identi cation for proteogenomics studies. We have developed computational methods and software tools for protein identification and quantitation. In addition, we also design algorithms that facilitate variant peptide identi cation and propose rigorous analytical procedures for further con rming variant peptides identi ed from MS data. Currently, we are participating in Taiwan Cancer Moonshot Project to study lung cancer and the Chromosome-centric Human Proteome Project to study missing proteins. Publications 1. Wai-Kok Choong, Ching-Tai Chen, Jen-Hung Wang, and Ting- using DYAMOND algorithm,\" Analytical Chemistry, vol. 89, no. Brochure 2020 Yi Sung, \"iHPDM: in silico human proteome digestion map with 24, pp. 13128-13136, Dec. 2017. proteolytic peptide analysis and graphical visualizations,\" Journal of Proteome Research, vol. 18, no. 12, pp. 4124-4132, Dec. 2019. 7. T. Mamie Lih, Wai-Kok Choong, Chen-Chun Chen, Cheng- Wei Cheng, Hsin-Nan Lin, Ching-Tai Chen, Hui-Yin Chang, 2. Thejkiran Pitti, Ching-Tai Chen, Hsin-Nan Lin, Wai-Kok Wen-Lian Hsu, and Ting-Yi Sung, \"MAGIC-web: a platform for Choong, Wen-Lian Hsu, and Ting-Yi Sung, \"N-GlyDE: a two- untargeted and targeted N-linked glycoprotein identification,\" stage N-linked glycosylation site prediction incorporating gapped Nucleic Acids Research , vol. 44, Web Server Issue, pp. W575- dipeptides and pattern-based encoding,\" Scientific Reports, vol. 9, 580, 2016. pp. 15975, Nov. 2019. 8. Hui-Yin Chang, Ching-Tai Chen, T. Mamie Lih, Ke-Shiuan Lynn, 3. Ching-Tai Chen, Chu-Ling Ko, Wai-Kok Choong, Jen-Hung Chiun-Gung Juo, Wen-Lian Hsu, and Ting-Yi Sung, \"iMet-Q: a Wang, Wen-Lian Hsu, and Ting-Yi Sung, \"WinProphet: a user- user-friendly tool for metabolomics quantitation using dynamic friendly pipeline management system for proteomics data analysis peak-width determination,\" PLoS ONE , vol. 11, no. 1, pp. based on Trans-Proteomic Pipeline,\" Analytical Chemistry, vol. e0146112, Jan. 2016. 91, no. 15, pp. 9403-9406, Aug. 2019. 9. Wai-Kok Choong, Hui-Yin Chang, Ching-Tai Chen, Chia-Feng 4. T. Mamie Lih, Wai-Kok Choong, Yu-Ju Chen, and Ting-Yi Tsai, Wen-Lian Hsu, Yu-Ju Chen, and Ting-Yi Sung, \"Informatics Sung, \"Evaluating the possibility of detecting variants in shotgun view on the challenges of identifying missing proteins from proteomics via LeTE-fusion analysis pipeline,\" Journal of shotgun proteomics,\" Journal of Proteome Research, vol. 14, no. Proteome Research, vol. 17, no. 9, pp. 2937-2952, Sep. 2018. 12, pp. 5396-5407, Dec. 2015. 5. Wai-Kok Choong, T. Mamie Lih, Yu-Ju Chen, and Ting-Yi Sung, 10. Ke-Shiuan Lynn, Chen-Chun Chen, T. Mamie Lih, Cheng-Wei \"Decoding the effect of isobaric substitutions on identifying Cheng, Wan-Chih Su, Chun-Hao Chang, Chia-Ying Cheng, missing proteins and variant peptides in human proteome,\" Wen-Lian Hsu, Yu-Ju Chen, and Ting-Yi Sung, \"MAGIC: an Journal of Proteome Research, vol. 16, no. 12, pp. 4415-4424, automated N-linked glycoprotein identification tool using a Y1- Dec. 2017 ion pattern matching algorithm and in silico MS2 approach,\" Analytical Chemistry, Vol. 87, No. 4, pp. 2466-2473, Feb. 2015. 6. Hui-Yin Chang, Ching-Tai Chen, Chu-Ling Ko, Yi-Ju Chen, Yu- Ju Chen, Wen-Lian Hsu, Chiun-Gung Juo, and Ting-Yi Sung, \"iTop-Q: an intelligent tool for top-down proteomics quantitation 159

究研 人 Research Fellow 員 李丕榮 PeiZong Lee Faculty Ph.D., Computer Science, New York University, United States T +886-2-2788-3799 ext. 1812 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/leepe/ ・ Research Fellow, Academia Sinica, Taiwan (1998/1-present) ・ Adjunct Associate Professor, Department of Electrical Engineering, National Chung Cheng University, Chiayi, Taiwan (1993-1996) ・ Associate Research Fellow, Academia Sinica, Taiwan (1989/10-1998/1) Research Description My research interests are in compilers for scienti c applications, parallel algorithm design, computer architectures, and the interplay among architectures, algorithms, and compilers. The challenge of implementing large scienti c applications for current parallel computers is to handle data locality among memory hierarchies, so that to avoid memory conflict on shared memory parallel computers and to avoid communication overhead on distributed memory parallel computers. Compilers act as bridges connecting algorithms and architectures. I am interested in studying this interdependence. For running on distributed memory parallel computers, if a program does not use indirect memory accesses, such as subscript array of arrays or pointers, compilers can nd data dependence relations among statements and data alignment relations among data arrays. Therefore, compilers have enough information to determine data distribution, execution scheduling, and the generation of communication code using e ective communication primitives. However, if a program does use subscript array of arrays or pointers to implement indirect memory accesses for irregular computation, compilers at the compiling time cannot determine neither data dependence relations nor data alignment relations; if compilers only provide naïve data distributions, generated code cannot avoid adopting expensive communication primitives which de nitely lengthen the execution time and thus degrade the performance of parallel processing. To understand the techniques for compiling irregular computation, we analyze real code for scienti c computation, in which we have to conduct research into unstructured mesh generation; unstructured mesh partition; Euler equation and Navier- Stokes equation solvers for a numerical wind tunnel platform, an engine combustion platform for computing reactive ows; visualization; and the challenge of using MPI on multi-core workstation/PC clusters to accelerate irregular computation. Our target is to provide paradigms for designing di erent classes of computation-intensive applications, so that compilers can automatically generated e cient code for parallel computation. Publications 1. PeiZong Lee and Zvi M. Kedem. 1988. \"Synthesizing Linear- Parallel and Distributed Systems, Vol. 8, No. 8, Aug. 1997, page Array Algorithms from Nested For Loop Algorithms,\" in The 825-839. Special Issue on Parallel and Distributed Algorithms, IEEE Transactions on Computers, Vol. C-37, No. 12, Dec. 1988, page 7. P e i Z o n g L e e a n d We n - Ya o C h e n . 2 0 0 2 . \" G e n e r a t i n g 1578-1598. Communication Sets of Array Assignment Statements for Block- Cyclic Distribution on Distributed Memory Parallel Computers,\" 2. PeiZong Lee and Zvi M. Kedem. 1990. \"Mapping Nested Loop Parallel Computing, Vol. 28, No. 9, Sep. 2002, page 1329-1368. Algorithms into Multidimensional Systolic Arrays,\" in IEEE Transactions on Parallel and Distributed Systems, Vol. 1, No. 1, 8. PeiZong Lee and Zvi M. Kedem. 2002. \"Automatic Data and Jan. 1990, page 64-76. Computation Decomposition on Distributed Memory Parallel Computers,\" ACM Transactions on Programming Languages and 3. PeiZong Lee and Fang-Yu Huang. 1994. \"Restructured Recursive Systems, Vol. 24, No. 1, Jan. 2002, page 1-50. DCT and DST Algorithms,\" in IEEE Transactions on Signal Processing, Vol. 42, No. 7, July 1994, page 1600-1609. 9. PeiZong Lee, Chih-Hsueh Yang, and Jeng-Renn Yang. 2004. \"Fast Algorithms for Computing Self-Avoiding Walks and 4. PeiZong Lee and Fang-Yu Huang. 1994. \"An Efficient Prime- Mesh Intersections over Unstructured Meshes,\" Advances in Factor Algorithm for the Discrete Cosine Transform and Its Engineering Software, Vol. 35, No. 2, Feb. 2004, page 61-73. Hardware Implementations,\" IEEE Transactions on Signal Processing, Vol. 42, No. 8, Aug. 1994, page 1996-2005. 10. PeiZong Lee, Chien-Min Wang, and Jan-Jan Wu. 2006. \"Compiler and Run-time Parallelization Techniques for Scientific 5. PeiZong Lee. 1995. \"Techniques for Compiling Programs on Computations on Distributed Memory Parallel Computers,\" Distributed Memory Multicomputers,\" Parallel Computing, Vol. included in the book High Performance Computing: Paradigm 21, No. 12, Dec. 1995, page 1895-1923. and Infrastructure, pp. 135-181, edited by Dr. Laurence T. Yang and Dr. Minyi Guo, John Wiley & Sons, Inc., 2006. 6. PeiZong Lee. 1997. \"Efficient Algorithms for Data Distribution on Distributed Memory Multicomputers,\" IEEE Transactions on 160

Research Fellow 林仲彥 研 究 Chung-Yen Lin 人 員 Ph.D., Zoology, National Taiwan University, Taiwan Faculty T +886-2-2788-3799 ext. 1704 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/cylin ・ Research Fellow (2020-present), Associate Research Fellow (2010), Assistant Research Fellow (2005), Institute of Information Science, Academia Sinica, Taiwan ・ Joint-appointed Associate Principal Investigator(2011-present), Assistant Research Fellow (2003), Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan ・ Joint-appointed Professor (2020-present), Associate Professor (2012), Assistant Professor (2005), Institute of Fishery Science & Program of Genome and Bioinformatics, National Taiwan University, Taiwan ・ Awards Winner for Future Tech Breakthrough Award by the Ministry of Science and Technology, Taiwan (2018) and National Innovation Award by Research Center for Biotechnology and Medicine Policy, Taipei, Taiwan (2018, 2019) Research Description Our research is motivated by a desire to utilize IT innovations to bridge computer science, high-dimensional statistics, and genomics, then decipher the secrets of nature and make life better. In recent years, our works have focused on the following areas: (1) Network analyses in tumorigenesis and infectious diseases, (2) Developing value-added databases/web applications for biomedical research communities, (3) Using Machine learning/AI to decipher the biological problems like smart typing of pathogens, design of new antimicrobial peptides, etc. All of the published results have been converted into useful web applications/databases/dockers for active use by research communities worldwide since 2003. Many of our databases/applications are listed on several Bioinformatics portals with accumulated users and processed sequences around 400,000 and 2,200,000, respectively. Over the past five years, we have published 16 SCI papers (16 on open assess journals, 15 belonged to Q1, ve as rst/corresponding author) with seven new and over ten previous works as web databases/applications, several standalone software, and one technology transfer (to Welgene Inc.). One of our e orts, cytohubba (http://apps.cytoscape.org/apps/ cytohubba), which can detect important nodes and subnetworks in a given network by several topological algorithms, has been downloaded over 20,000 times with near 350 citations since it released in Jan 2017. Publications 1. Sheng-Yao Su, I-Hsuan Lu, Wen-Chih Cheng, Wei-Chun Chung, Gene Profiling Deconvolution Approach to Estimate Immune Brochure 2020 Pao-Yang Chen, Jan-Ming Ho, Shu-Hwa Chen, Chung-Yen Lin*, Cell Composition from Complex Tissues,\" BMC Bioinformatics, \"An Intuitive Web-based Framework for Genome-wide DNA volume 19, number (Suppl 4), pages 154, May 2018 Methylation Analysis,\" to appear in BMC Genomics , Website: http://symbiosis.iis.sinica.edu.tw/epimolas/molas.html 7. Hsiao-Pei Lu, Po-Yu Liu, Yu-bin Wang, Ji-Fan Hsieh, Han-Chen Ho, Shiao-Wei Huang, Chung-Yen Lin, Chih-hao Hsieh, Hon- 2. Wen-Chun Huang, Chung-Yen Lin, Masayuki Hashimoto, Jiunn- Tsen Yu, \"Functional Characteristics of the Flying Squirrels Cecal Jong Wu, Ming-Cheng Wang, Wei-Hung Lin, Chang-Shi Chen Microbiota under a Leaf-Based Diet, Based on Multiple Meta- & Ching-Hao Teng, \"The role of the bacterial protease Prc in the Omic Profiling,\" Frontiers in Microbiology, volume 8, pages uropathogenesis of extraintestinal pathogenic Escherichia coli,\" 2622, January 2018. Journal of Biomedical Science, volume 27, number 14, pages 1-22, January 2020, (IF= 5.2) . 8. Hangfei Qi, Virginia Chu, Nicholas C. Wu, Zugen Chen, Shawna Truong, Gurpreet Brar, Sheng-Yao Su, Yushen Du, Vaithilingaraja 3. Reuben Wang, Chung-Yen Lin, Shu-Hwa Chen, Kai-Jiun Arumugaswami, C. Anders Olson, Shu-Hua Chen, Chung-Yen Lo, Chi-Te Liu, Tzu-Ho Chou, Yang-hsin Shih, \"Using high- Lin, Ting-Ting Wu, and Ren Sun, \"Systematic identification of throughput transcriptome sequencing to investigate the anti-interferon function on hepatitis C virus genome reveals p7 biotransformation mechanism of hexabromocyclododecane with as an immune evasion protein,\" Proceedings of the National Rhodopseudomonas palustris in water,\" Science of the Total Academy of Sciences of the United States of America (PNAS), Environment, volume 692, pages 249-258, November 2019, volume 114, number 8, pages 2018-2023, February 2017, (IF=5.6) Collaboration with team in UCLA. 4. Li-An Yang, Yu-Jung Chang, Shu-Hwa Chen, Chung-Yen Lin 9. Sheng-Yao Su, Shu-Hwa Chen, I-Hsuan Lu, Yih-Shien Chiang, and Jan-Ming Ho, \"SQUAT: A Sequencing Quality Assessment Yu-Bin Wang, Pao-Yang Chen, Chung-Yen Lin*, \"TEA: The Tool for Data Quality Assessments before and after Genome Epigenome platform for Arabidopsis methylome study,\" BMC Assemblies,\" BMC Genomics, volume 19, number Suppl 9, pages Genomics , volume 17(S13), pages 1027, December 2016, Tea 238, April 2019, Open Access website: http://tea.iis.sinica.edu.tw icon 5. Tsung-Chieh Yao, Ren-Hua Chung, Chung-Yen Lin, et al., 10. Anderson B. Mayfield, Yu-Bin Wang, Chii-Shiarng Chen, \"Genetic Loci Determining Total Immunoglobulin E from Birth Shu-Hwa Chen, and Chung-Yen Lin*, \"Dual-compartmental through Adulthood Identified from Genome-wide Association transcriptomic + proteomic analysis of a marine endosymbiosis Study of Asians,\" Allergy , volume 1, number 4, pages 1-4, exposed to environmental change,\" Molecular Ecology, volume November 2018, (IF:6.08) 25, number 23, pages 5944-5958, November 2016, the web database can be found at http://symbiont.iis.sinica.edu.tw/s_ 6. Shu-Hwa Chen, Wen-Yu Kuo, Sheng-Yao Su, Wei-Chun Chung, hystrix (IF: 5.98) Jen-Ming Ho, Henry Horng-Shing Lu, Chung-Yen Lin*, \"A 161

究研 人 Assistant Research Fellow 員 林仁俊 Jen-Chun Lin Faculty Ph.D., Computer Science and Information Engineering, National Cheng Kung University, Taiwan T +886-2-2788- 3799 ext.1804 E [email protected] F +886-2-2782-4814 W wjenwcwh.uiins.lsiinn/iicnad.eedxu_z.thw.h/ptmagl es/ ・ Sadaoki Furui Prize Paper Award, APSIPA (2018) ・ Postdoctoral Academic Publication Award, MOST (2017) ・ Most Interesting Paper Award, ASMMC (2015) ・ Gold Thesis Award, Merry Electronics (2014) ・ Excellent PhD Dissertation Award, IPPR (2014) ・ Excellent PhD Dissertation Award, TAAI (2014) ・ Assistant Professor, Department of Electrical Engineering, Yuan Ze University (2018- 2020) ・ Postdoc, Institute of Information Science, Academia Sinica (2014-2018) Research Description My research focuses on multimedia content understanding, machine learning, and a ective computing. I am passionate about building systems that can engage users with multimedia. In view of that the aforementioned issue relies heavily on the association between visual and auditory, my research e orts also take this perspective into account in designing machine learning techniques, ranging from low-level to high-level, to more appropriately bridge the relationship between video and audio. Although my current research focuses on video and audio I am also interested in other modalities such as text. Creating a system capable of engaging users with multiple signals is my research mission. Publications 1. Jen-Chun Lin, Wen-Li Wei, Tyng-Luh Liu, C.-C. Jay Kuo, 6. Jen-Chun Lin, Wen-Li Wei, and Hsin-Min Wang, \"EMV- and Hong-Yuan Mark Liao, \"Tell Me Where It is Still Blurry: matchmaker: Emotional Temporal Course Modeling and Adversarial Blurred Region Mining and Refining,\" ACM Matching for Automatic Music Video Generation,\" ACM Multimedia, Nice, France, October 2019. Multimedia, Brisbane, Australia, October 2015. 2. Jen-Chun Lin, Wen-Li Wei, Tyng-Luh Liu, Yi-Hsuan Yang, 7. Chung-Hsien Wu, Jen-Chun Lin, and Wen-Li Wei, \"Survey on Hsin-Min Wang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao, Audiovisual Emotion Recognition: Databases, Features, and \"Coherent Deep-Net Fusion to Classify Shots in Concert Videos,\" Data Fusion Strategies,\" APSIPA Transactions on Signal and IEEE Transactions on Multimedia, vol. 20, no. 11, pp. 3123-3136, Information Processing, vol. 3, no.12, pp. 1-18, 2014. 2018. 8. Wen-Li Wei, Chung-Hsien Wu, Jen-Chun Lin, and Han 3. Jen-Chun Lin, Wen-Li Wei, James Yang, Hsin-Min Wang, and Li, \"Exploiting Psychological Factors for Interaction Style Hong-Yuan Mark Liao, \"Automatic Music Video Generation Recognition in Spoken Conversation,\" IEEE Transactions on Based on Simultaneous Soundtrack Recommendation and Video Audio, Speech and Language Processing, vol. 22, no. 3, pp. 659- Editing,\" ACM Multimedia, Mountain View, CA, USA, October 671, 2014. 2017. 9. Chung-Hsien Wu, Jen-Chun Lin, and Wen-Li Wei, \"Two- 4. Wen-Li Wei, Jen-Chun Lin, and Chung-Hsien Wu, \"Interaction Level Hierarchical Alignment for Semi-Coupled HMM-Based Style Recognition Based on Multi-layer Multi-view Profile Audiovisual Emotion Recognition with Temporal Course,\" IEEE Representation,\" IEEE Transactions on Affective Computing, vol. Transactions on Multimedia, vol. 15, no. 8, pp. 1880-1895, 2013. 8, no. 3, pp. 355-368, 2017. 10. Jen-Chun Lin, Chung-Hsien Wu, and Wen-Li Wei, \"Error 5. Jen-Chun Lin, Wen-Li Wei, and Hsin-Min Wang, \"Automatic Weighted Semi-Coupled Hidden Markov Model for Audio-Visual Music Video Generation Based on Emotion-Oriented Pseudo Emotion Recognition,\" IEEE Transactions on Multimedia, vol. Song Prediction and Matching,\" ACM Multimedia, Amsterdam, 14, no. 1, pp. 142-156, 2012. The Netherlands, October 2016. 162

Research Fellow 施純傑 研 究 Arthur Chun-Chieh Shih 人 員 Ph.D., Computer Science and Information Engineering, Faculty National Central University, Taiwan T +886-2-2788-3799 ext. 2470 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/arthur ・ Research Fellow, IIS, Academia Sinica (2014-present) ・ Associate Research Fellow, IIS, Academia Sinica (2008-2014) ・ Assistant Research Fellow, IIS, Academia Sinica (2002-2008) ・ Postdoctoral Fellow, Department of Ecology and Evolution, University of Chicago (2001-2002) ・ Postdoctoral Fellow, IIS, Academia Sinica (1998-2001) ・ Ph.D. Computer Science and Information Engineering, National Central University (1998) ・ Academia Sinica Career Development Award (2010) Research Description In the past decade, my research interests focused on the development of computational tools for processing biological big data and the study of biological issues related to molecular evolution and genetic regulatory networks. The major computational challenge that we face was to design methods that can be executed e ciently and e ectively solve important biological problems. On the other hand, the main challenges for our biological studies included analyzing and extracting meaning from patterns within large data sets, while at the same time, proposing testable hypotheses to explain natural mechanisms. With regard to the tool development, we have created powerful tools for genomic sequence alignment (GS-Aligner), visualization of sequence alignment results (SinicView and Phylo-mLogo), identifying the breakpoints of rearrangement events (GR-Aligner), and assembly of a giga-base-pair genome from lllumina short reads (JR-Assembler). In addition, a new method for assembling short sequences from RNA-seq (JR-Trans) has been also developed recently. In the collaboration with biologists from various institutes and research centers in Academia Sinica, we have used computational approaches and made signi cant discoveries related to gene regulation in C4 plant leaf development, gene duplication in C4 plant photosynthesis evolution, miRNA regulatory networks in B cell di erentiation, and genetic regulatory networks in cardiac hypertrophy. Currently, my research interests have been changed to the eld of optogenetics in observing neural activities in nervous systems. We are going to develop a low-cost uorescent mouse head-mounted miniature microscope and related image processing techniques that can be applied to observe neuron activity in brain in a freely moving mouse, especially in chronic pain study. 1. Yao-Ming Chang, Li Ling, Ya-Ting Chang, Yu-Wang Chang, Publications Brochure 2020 Wen-Hsiung Li, Arthur Chun-Chieh Shih*, and Chien-Chang Chen*, \"Three TF Co-expression Modules Regulate Pressure- 6. Yao-Ming Chang, Hsueh-Fen Juan, Tzu-Ying Lee, Ya-Ya Chang, Overload Cardiac Hypertrophy in Male Mice,\" Scientific Reports Yao-Ming Yeh, Wen-Hsiung Li*, and Arthur Chun-Chieh Shih*, 7: 7560, 2017. \"Prediction of human miRNAs using tissue-selective motifs in 3' UTRs,\" Proceedings of the National Academy of Sciences 2. Tong-Yen Tsai, Shih-Ying Wu, Cheng-Han Chung, Pang-Yen 105(44): 17061-17066, 2008. Yang, Shin-Tang Su, Yu-Hsuan Tseng, Tong-Cheng Wang, Wen-Hsiung Li, Arthur Chun-Chieh Shih*, and Kuo-I Lin*, 7. Arthur Chun-Chieh Shih, Tze-Chang Shiao, Mei-Shang Ho, and \"Uncovering MicroRNA Regulatory Hubs that Modulate Plasma Wen-Hsiung Li, \"Simultaneous Amino Acid Substitutions at Cell Differentiation,\" Scientific Reports 5: 17957, 2015. Antigenic Sites Drive Influenza A Hemagglutinin Evolution,\" Proceedings of the National Academy of Sciences 104(15): 6283- 3. Te-Chin Chu, Chen-Hua Lu, Tsunglin Liu, Greg C. Lee, Wen- 6288, 2007. Hsiung Li* and Arthur Chun-Chieh Shih*, \"Assembler for de novo assembly of large genomes.\" Proceedings of the National 8. Arthur Chun-Chieh Shih, D.T. Lee, Chin-Lin Peng, and Yu-Wei Academy of Sciences 110(36): E3417-3424, 2013. Wu, \"Phylo-mLogo: An interactive multiple-logo visualization tool for large-number sequence alignments\", BMC Bioinformatics 4. Yao-Ming Chang, Chia-Lin Chang, Wen-Hsiung Li, Arthur Chun- 8:63, 2007. Chieh Shih*, \"Historical Profiling of Maize Duplicate Genes Sheds Light on the Evolution of C4 Photosynthesis in Grasses,\" 9. Arthur Chun-Chieh Shih, D.T. Lee, Laurent Lin, Chin-Lin Peng, Molecular Phylogenetics and Evolution 66(2): 453-462, 2013. Shiang-Heng Chen, Yu-Wei Wu, Chun-Yi Wong, Meng-Yuan Chou, Tze-Chang Shiao, and Mu-Fen Hsieh, \"SinicView: A 5. Te-Chin Chu, Tsunglin Liu, D.T. Lee, Greg C. Lee, and Arthur visualization environment for comparisons of multiple nucleotide Chun-Chieh Shih*, \"GR-Aligner: an algorithm for aligning sequence alignment tools,\" BMC Bioinformatics 7:103, 2006. pairwise genomic sequences containing rearrangement events,\" Bioinformatics 25(17): 2188-2193, 2009. 10. Arthur Chun-Chieh Shih and Wen-Hsiung Li, \"GS-Aligner: A Novel Tool for Aligning Genomic Sequences Using Bit-Level Operations,\" Molecular Biology and Evolution 20(8): 1299-1309, 2003. 163

究研 人 Assistant Research Fellow 員 柯向上 Hsiang-Shang 'Josh' Ko Faculty DPhil, Computer Science, University of Oxford, United Kingdom T +886-2-2788-3799 ext. 1719 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/joshko ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica, Taiwan (2019-present) ・ Assistant Professor by Special Appointment, National Institute of Informatics, Japan (2017-2019) ・ Researcher by Special Appointment, National Institute of Informatics, Japan (2014-2017) Research Description I am interested in the discovery of mathematical and logical structures of computation so that they can be manifested in programming languages and effectively guide the programmer. I approach problems mainly from the perspective of intuitionistic type theory, which substantially overlaps with functional programming. For theoretical modelling, my weapon of choice is the dependently typed language Agda; for practical programming, I use the functional language Haskell. I have been exploring the potential of dependently typed programming, where sophisticated correctness properties and proofs can be integrated into types and programs, and mechanically verified by type-checking. More interestingly, with an interactive development environment (like the Emacs mode o ered by Agda) that provides semantic hints in the form of type information, the programmer can gain better \"situation awareness\" regarding the meaning of the program being constructed. This is made possible primarily because of inductive families, and my DPhil thesis developed datatype-generic techniques for improving usability and reusability of inductive families. I also studied the Algebra of Programming (also known as Bird-Meertens formalism or program calculation) and contributed to its dependently typed formalisation. I have also worked on bidirectional transformations for solving consistency maintenance (synchronisation) problems. More speci cally, my focus was on bidirectional programming, which is largely synonymous with the construction of lenses (introduced by Foster et al at POPL 2005). My main results in this area were built around a small \"putback-based\" bidirectional programming language BiGUL (Bidirectional Generic Update Language), about which there were an Agda formalisation, a Haskell port, and an axiomatic semantics that helps to explain how to think about bidirectional programs unidirectionally. I was also involved in some joint work on the applications of bidirectional programming, notably the uni cation of parsing and \"retentive/re ective\" printing with certain guarantees of \"well-behavedness\". Publications 1. Zirun Zhu, Hsiang-Shang Ko, Yongzhe Zhang, Pedro Martins, Computer Science, pages 301-320. Springer, 2017. https://doi. João Saraiva, and Zhenjiang Hu. Unifying parsing and reflective org/10.1007/978-3-319-71237-6_15 printing for fully disambiguated grammars. To appear in New Generation Computing . https://doi.org/10.1007/s00354-019- 6. Hsiang-Shang Ko and Jeremy Gibbons. Programming with 00082-y ornaments. Journal of Functional Programming, 27:e2, 2017. https://doi.org/10.1017/S0956796816000307 2. Anthony Anjorin, Thomas Buchmann, Bernhard Westfechtel, Zinovy Diskin, Hsiang-Shang Ko, Romina Eramo, Georg Hinkel, 7. Hsiang-Shang Ko, Tao Zan, and Zhenjiang Hu. BiGUL: A Leila Samimi-Dehkordi, and Albert Zündorf. Benchmarking formally verified core language for putback-based bidirectional bidirectional transformations: Theory, implementation, programming. In Workshop on Partial Evaluation and Program application, and assessment. Software and Systems Modeling, Manipulation (PEPM), pages 61-72. ACM, 2016. https://doi. 2020. https://doi.org/10.1007/s10270-019-00752-x org/10.1145/2847538.2847544 3. Zhenjiang Hu and Hsiang-Shang Ko. Principles and practice of 8. H s i a n g - S h a n g K o a n d J e r e m y G i b b o n s . R e l a t i o n a l bidirectional programming in BiGUL. In International Summer algebraic ornaments. In Workshop on Dependently Typed School on Bidirectional Transformations (Oxford, UK, 25- Programming (DTP), pages 37-48. ACM, 2013. https://doi. 29 July 2016), volume 9715 of Lecture Notes in Computer org/10.1145/2502409.2502413 Science, chapter 4, pages 100-150. Springer, 2018. https://doi. org/10.1007/978-3-319-79108-1_4 9. Hsiang-Shang Ko and Jeremy Gibbons. Modularising inductive families. Progress in Informatics, 10:65-88, 2013. https://doi. 4. Hsiang-Shang Ko and Zhenjiang Hu. An axiomatic basis org/10.2201/NiiPi.2013.10.5 for bidirectional programming. Proceedings of the ACM on Programming Languages, 2(POPL):41, 2018. https://doi. 10. Shin-Cheng Mu, Hsiang-Shang Ko, and Patrik Jansson. Algebra org/10.1145/3158129 of Programming in Agda: Dependent types for relational program derivation. Journal of Functional Programming, 19(5):545-579, 5. Yongzhe Zhang, Hsiang-Shang Ko, and Zhenjiang Hu. Palgol: A 2009. https://doi.org/10.1017/S0956796809007345 high-level DSL for vertex-centric graph processing with remote data access. In Asian Symposium on Programming Languages and Systems (APLAS), volume 10695 of Lecture Notes in 164

Research Fellow 徐讚昇 研 究 Tsan-sheng Hsu 人 員 Ph.D., Computer Sciences, University of Texas at Austin, United States Faculty T +886-2-2788-3799 ext. 1701 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/tshsu ・ Professor (Adjunct), Computer Science and Information Engineering, National Taiwan University (2004-present) ・ Editor-in-Chief, Journal of Information Science and Engineering (2019-present) ・ Editor, Information Processing letters (2011-2017) ・ Acting Chief, Information Center, Institute of Information Science, Academia Sinica (2013-2015) ・ Director, Computing Center, Academia Sinica (2008-2010) ・ Deputy Director, Institute of Information Science, Academia Sinica (2002-2004) ・ M.S.C.S., Computer Sciences, University of Texas at Austin (1990) ・ B.S., Computer Science and Information Engineering, National Taiwan University (1985) Research Description My current work concerns graph theory and its applications, the design, analysis, implementation and performance evaluation of algorithms, and data-intensive computing. Graph theory and its applications: Graphs model many important applications and are also tools that may be used to solve theoretical problems. We often begin our research by probing fundamental theoretical problems, such as the structures of graphs with certain properties. With these properties, we then usually design e cient algorithms and solve applications. One important problem we are currently interested in is e cient graph algorithms on the streaming model. Design, analysis, implementation and performance evaluation of algorithms: Algorithm is one of the cores of computer sciences. We are interested in all aspects of research on algorithms, including finding new algorithms for interesting problems and designing e cient implementations to solve real-world applications. We are interested in sequential, parallel and distributed algorithms. For example, we are now studying e cient implementation of graph algorithms on GPUs. Data-intensive computing: With the rapid development of computer and communication technology, it has become much easier to access and store massive amounts of data electronically. We are interested in research problems concerning efficient computation of massive data, which include classical computer games, and constructing and viewing of medical-related big data. In classical computer games, we currently focus on a stochastic two-player game called Chinese Dark Chess, and on extremely large endgame databases of various games. In medical-related big data, we have been working on e cient epidemic simulation, disease networks and risk prediction. Notably, our research in data-intensive computing often overlaps and bene ts from our studies of graph theory and algorithm. Publications 1. Jr-Chang Chen, Ting-Yu Lin, Bo-Nian Chen, and Tsan-sheng 6. Zong-De Jian, Hung-Jui Chang, Tsan-sheng Hsu and Da-Wei Brochure 2020 Hsu,\"Equivalence Classes in Chinese Dark Chess Endgames,\" Wang,\"Learning from Simulated World - Surrogates Construction IEEE Transactions on Computational Intelligence and AI in with Deep Neural Network,\" Proceedings of the 7th International Games, volume 7, number 2, pages 109--122, June 2015, DOI: Conference on Simulation and Modeling Methodologies, 10.1109/TCIAIG.2014.2317832. Technologies and Applications (SIMULTECH), July 2017, Best paper award. 2. Martin Farach-Colton, Tsan-sheng Hsu, Meng Li and Meng- Tsung Tsai,\"Finding Articulation Points of Large Graphs in 7. Hung-Jui Chang, Jr-Chang Chen, Gang-Yu Fang, Chih- Linear Time,\" Proceedings of WADS 2015 : Algorithms and Data Wen Hsueh and Tsan-sheng Hsu,\"Using Chinese Dark Chess Structu res Symposium, number 9214, LNCS, Springer, pages Endgame Databases to Validate and Fine-Tune Game Evaluation 363--372, August 2015. Functions,\" International Computer Game Association (ICGA) Journal, volume 40, pages 45--60, June 2018. 3. H u n g - J u i C h a n g , C h i h - We n H s u e h a n d Ts a n - s h e n g Hsu,\"Convergence and Correctness Analysis of Monte-Carlo Tree 8. Jr-Chang Chen, Gang-Yu Fan, Hung-Jui Chang and Tsan-sheng search Algorithms: A Case Study of 2 by 4 Chinese Dark Chess,\" Hsu,\"Compressing Chinese Dark Chess Endgame Databases Proceedings of the 2015 IEEE Conference on Computational by Deep Learning,\" IEEE Transcations on Games , volume 10, Intelligence and Games (CIG), pages 260--266, August 2015, number 4, pages 413--422, December 2018. Best student paper award. 9. Hung-Jui Chang, YH Hsu, Chih-WeW Hsueh, Tsan-sheng 4. J Zong-De Jian, Tsan-sheng Hsu and Da-Wei Wang,\"Searching Hsu,\"Efficient qualitative method for matching subjects with Vaccination Strategy with Surrogate-assisted Evolutionary multiple controls,\" Proceedings of the Fifth International Computing,\" Proceedings of the 6th International Conference Conference on Big Data, Small Data, Linked Data and Open Data on Simulation and Modeling Methodologies, Technologies and (ALLDATA), CP Rückemann, editor, pages 46-51, March 2019. Applications (SIMULTECH), July 2016, Best paper award. Best paper award. 5. 5M.-L. Pan, H.-M. Tsao, C.-C. Hsu, K.-M. Wu, Tsan-sheng 10. Yi-Jun Chang, Martin Farach-Colton, Tsan-sheng Hsu and Hsu, Y.-T. Wu and G.-C. Hu, \"Bidirectional association between Meng-Tsung Tsai,\"Streaming Complexity of Spanning Tree obstructive sleep apnea and depression: A population-based Computation,\" Proceedings of the 37th International Symposium longitudinal study,\" Medicine , volume 95, number 37, pages on Theoretical Aspects of Computer Science (STACS) , pages e4833, September 2016. 34:1-34:19, 2020. 165

究研 人 Associate Research Fellow 員 馬偉雲 Wei-Yun Ma Faculty Ph.D., Computer Science, Columbia University, United States T +886-2-2788-3799 ext. 1819 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/ma ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica (2014-2020) ・ Ph.D., Computer Science, Columbia University (2014) ・ Top3 in the rst Formosa Grand Challenge-Talk to AI (2019) ・ PIXNET best product award for Chatbot (2017) ・ Best paper award in IALP (2017) ・ Best Demo - Special Mention Award at WWW (2017) Research Description My research interests include Natural Language Processing (NLP), Machine Learning, Deep Learning, Knowledge Graph, Dialog Agent and Question Answering. I am fascinated by the idea of giving computers the ability to understand human language. Recently I have mainly focused on NLP problems concerning knowledge-based information processing, a process which is strongly motivated by the deluge of information available on the Internet and knowledge bases. To develop a practical and high-quality knowledge base for the need of knowledge-based information processing is very critical and also challenging. The number of entities can be millions, ten millions, and even endless. It is impossible to build manually, so it must be built in an automated way. At the same time, its inference mechanism, including causality, relationships, action processes, etc. must also be considered together, so the representation form and the representation ability of such knowledge base also needs to be carefully designed. To build such a practical knowledge base, I am currently engaged in research on knowledge acquisition, representation, reasoning and utilization. I am also fascinated by addressing NLP tasks by utilizing deep reinforcement learning models, where the models concern with how software agents ought to take actions in an environment so as to maximize rewards. Publications on Asian Language Processing (IALP), December 2017, (received Best Paper, Top1 out of 96 accepted papers) 1. Mu Yang, Chi-Yen Chen, Yi-Hui Lee, Qian-Hui Zeng, and Wei- Yun Ma, \"Headword-Oriented Entity Linking: A New Entity 10. Peng-Hsuan Li, Ruo-Ping Dong, Yu-SiangWang, Ju-Chieh Chou, Linking Task with Dataset and Baseline,\" LREC, May 2020 Wei-Yun Ma, \"Leveraging Linguistic Structures for Named Entity Recognition with Bidirectional Recursive Neural Networks,\" 2. Peng-Hsuan Li, Tsan-Yu Yang, and Wei-Yun Ma, \"CA-EHN: International Conference on EMNLP, September 2017. Commonsense Analogy from E-HowNet,\" LREC, May 2020 11. Peng-Yu Chen, Yi-Hui Lee, Yueh-Han Wu, Wei-Yun Ma, \"IExM: 3. Peng-Hsuan Li, Tsu-Jui Fu, and Wei-Yun Ma, \"Why Attention? Information Extraction System for Movies,\" WWW 2017 Demo Analyze BiLSTM Deficiency and Its Remedies in the Case of Track (receive Best Demo - Special Mention Award), April 2017. NER,\" International Conference on AAAI, Feb 2020. 12. Hsin-Yang Wang, Wei-Yun Ma, \"Integrating Semantic Knowledge 4. Lifeng Jin, Linfeng Song, Yue Zhang, Kun Xu, Wei-Yun Ma, into Lexical Embeddings Based on Information Content Dong Yu, \"Relation Extraction Exploiting Full Dependency Measurement,\" International Conference on EACL, April 2017. Forests,\" International Conference on AAAI, Feb 2020. 13. Hsin-Yang Wang, Wei-Yun Ma, \"CKIP Valence-Arousal Predictor 5. Tsu-Hui Fu, Wei-Yun Ma, \"GraphRel: Modeling Text as for IALP 2016 Shared Task,\" International Conference on Asian Relational Graphs for Joint Entity and Relation Extraction,\" Language Processing (IALP) (Top 1 out of 22 international teams International Conference on ACL, July 2019. on Valence of IALP 2016 Sentiment Task), November 2016. 6. Tsu-Hui Fu, Wei-Yun Ma, \"Speed Reading: Learning to Read 14. Wei-Yun Ma and Kathleen McKeown, \"System Combination ForBackward via Shuttle,\" International Conference on EMNLP, for Machine Translation through Paraphrasing,\" Proceedings October 2018. of Conference on Empirical Methods in Natural Language Processing (EMNLP), September 2015. 7. Wei-Yun Ma and Yueh-Yin Shih, \"Extended HowNet 2.0 - An Entity-Relation Common-Sense Representation Model,\" LREC, 15. Wei-Yun Ma and Kathleen McKeown, \"Where's the Verb May 2018. Correcting Machine Translation During Question Answering,\" Proceedings of ACL-IJCNLP, July 2009. 8. Chi-Yen Chen, Wei-Yun Ma, \"Word Embedding Evaluation Datasets and Wikipedia Title Embedding for Chinese,\" LREC , May 2018. 9. Chi-Yen Chen, Wei-Yun Ma, \"Embedding Wikipedia Title Based on Its Wikipedia Text and Categories,\" International Conference 166

Research Fellow 高明達 研 究 Ming-Tat Ko 人 員 Ph.D., Computer Science, National Tsing-Hua University, Taiwan Faculty T +886-2-27883799 ext. 1821 E [email protected] F +886-227824814 W www.iis.sinica.edu.tw/pages/mtko ・ Research Fellow, Institute of Information Science, Academia Sinica (2000-present) ・ Associate Research Fellow, Institute of Information Science, Academia Sinica (1988- 2000) ・ Ph.D., Computer Science, National Tsing-Hua University (1988) ・ M.S., Mathematics, National Taiwan University (1982) ・ B. S., Mathematics, National Taiwan University (1979) Research Description My research interest has been on the design and analysis of algorithms and graph theory with application to the real world problems. The research topics include problems on computational geometry, optimization problems on graphs and algorithmic problems arisen from bioinformatics. On computation geometry, geometric p-center problems for facility location, signal network design for VLSI layout are studied. Theoretical optimization problems studied include Hamiltonian problems, domination problems, graph searching problems, secure set problems, isometric path cover problems on various special graphs. Algorithmic problems arisen from bioinformatics are focused on phylogeny construction and biological network analysis. On phylogeny construction, we have studied the tree root problem and its generalization, the Steiner root problem that is to find a phylogenetic tree such that its power contains the given graph as an induced subgraph. On the biological network analysis, we have studied the topological characteristic of protein objects, such as essential proteins, protein functional modules, in protein-protein interaction networks of model organisms and tried to render decent methods for predicting such protein objects. Recently, my interest shifts to computational linguistics especially on Taiwanese. 1. Chih-En Kuo, Yue-Li Wang, Jia-Jie Liu, Ming-Tat Ko, Publications \"Resequencing a Set of Strings Based on a Target String,\" Algorithmica, Vol. 72, Issue 2, pp. 430-449, June 2015. 7. Han-Kuen Liang, Chia-Mao Huang, Ming-Tat Ko, Jenn-Kang Hwang, \"Amino acid-coupling patterns in thermophilic proteins,\" 2. Maw-Shang Chang and Ming-Tat Ko and Hsueh-I Lu, \"Linear Proteins: Structure, Function and Genetics, Vol.59, Issue 1, pp. Time Algorithms for Tree Root Problems,\" Algorithmica, Vol. 71, 58-63, April, 2005. Issue 2, pp. 471-495, Feb. 2015. 8. Sun-Yuan Hsieh, Chin-Wen Ho, Tsan-sheng Hsu and Ming- 3. Chia-Hao Chin, Shu-Hwa Chen, Hsin-Hung Wu, Chin-Wen Tat Ko, \"Characterization of Efficiently Solvable Problems Ho, Ming-Tat Ko, Chung-Yen Lin, \"cytoHubba: identifying on Distance-Hereditary Graphs,\" SIAM Journal on Discrete hub objects and subnetworks from complex interactome,\" BMC Mathematics, Vol. 15, No. 4, pp. 488-518, 2002. Systems Biology, Vol. 8, number S4, pages S11, December 2014. 9. Li-Fen Chen, Hong-Yuan Mark Liao, Ming-Tat Ko, Ja-Chen Lin 4. Yue-Li Wang, Cheng-Ju Hsu, Jia-Jie Liu, Ming-Tat Ko, Fu-Hsing and Gwo-Jong Yu, \"A New LDA-based Face Recognition System Wang, \"The Composition Problem and Its Applications,\" IEEE Which Can Solve the Small Sample Size Problem,\" Pattern Transactions on Computers, Vol. 61, No. 12, pp.1813-1822, Dec. Recognition, Vol. 33, pp. 1713-1726, 2000. 2012. 10. Sun-Yuan Hsieh, Chin-Wen Ho, Tsan-sheng Hsu, Ming-Tat Ko 5. Chia-Hao Chin, Chin-Wen Ho, Ming-Tat Ko and Chung-Yen Lin, and Gen-Huey Chen, \"A Faster Implementation of Parallel Tree \"A hub-attachment based method to detect functional modules Contraction Scheme and Its Applications on Distance-Hereditary from confidence-scored protein interactions and expression Graphs,\" Journal of Algorithms, Vol. 35, pp. 50-81, 2000. profiles,\" BMC Bioinformatics , Vol. 11, No. S1, pages S25, January 2010. Brochure 2020 6. Hsin-Hung Chou, Ming-Tat Ko, Chin-Wen Ho, and Gen-Huey Chen, \"Node- Searching Problem on Block Graphs,\" Discrete Applied Mathematics, Vol. 156, No. 1, pp. 55-75, January 2008. 167

究研 人 Research Fellow 員 張原豪 Yuan-Hao Chang Faculty Ph.D., Computer Science and Information Engineering, National Taiwan University, Taiwan T +886-2-2788-3799 ext. 1612 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/johnson ・ Research Fellow (2018-present) & Deputy Director (2019-present), Institute of Information Science, Academia Sinica ・ Best Paper Award, ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) (2019) ・ Best Paper Award, IEEE Non-Volatile Memory Systems and Applications Symposium (NVMSA) 2019 ・ Best paper nomination, ACM/IEEE Design Automation Conference (DAC) (2016) ・ Ta-You Wu Memorial Award, Ministry of Science and Technology (MOST) (2016) Research Description My research area is mainly on embedded systems, with a prime focus on improving the performance, reliability, and endurance of their storage systems with di erent types of non-volatile memories. It later grows to consider byte-addressable non-volatile memory (NVM) as both main memory and storage of embedded systems. Embedded systems, such as battery-powered consumer electronics and mobile computing systems, usually adopt flash storage devices as their storage systems. The fast-growing need of storage capacity drives the development of multi-level-cell (MLC) ash memory and 3D ash memory. However, due to the shrinking of the fabrication process and the advances of manufacturing technology to increase the density and capacity of ash chips, the performance, reliability, and endurance of MLC and 3D ash chips have become major design issues in related product designs. To address the above issues, we are interested in the solution at the storage device level. Our research goal is to resolve these issues with management designs in the software/ rmware layer of ash storage devices. On the other hand, existing le systems do not take the special characteristics of NVMs into consideration. As a result, when di erent NVMs are adopted as the storage media in di erent systems, the nice features of NVMs (e.g., byte-addressability and fast random access) might not be fully utilized, and the drawbacks of NVMs are not carefully tackled as well. Thus, in this research direction, we are interested in the le system design and optimization for NVM-based storage systems by utilizing the nice features of NVMs and resolving the drawbacks of NVMs. In particular, we pay more attention on addressing the space utilization and write ampli cation issues because embedded systems usually have limited energy and storage capacity. Publications 1. Shuo-Han Chen, Yen-Ting Chen, Yuan-Hao Chang, Hsin-Wen 6. Che-Wei Tsao, Yuan-Hao Chang, and Tei-Wei Kuo, \"Boosting Wei, and Wei-Kuan Shih, \"A Progressive Performance Boosting NVDIMM Performance with a Light-Weight Caching Algorithm,\" Strategy for 3D Charge-trap NAND Flash,\" IEEE Transactions on IEEE Transactions on Very Large Scale Integration Systems Very Large Scale Integration Systems (TVLSI) , vol. 26, no. 11, (TVLSI), vol. 26, no. 8, pp. 1518-1530, Aug. 2018. pp. 2322-2334, Nov. 2018. 7. Tseng-Yi Chen, Yuan-Hao Chang, Shuo-Han Chen, Chih-Ching 2. Wei-Chen Wang, Chien-Chung Ho, Yuan-Hao Chang, Tei-Wei Kuo, Ming-Chang Yang, Hsin-Wen Wei, and Wei-Kuan Shih, Kuo, and Ping-Hsien Lin, \"Scrubbing-aware Secure Deletion \"wrJFS: A Write-Reduction Journaling File System for Byte- for 3D NAND Flash,\" IEEE Transactions on Computer-Aided addressable NVRAM,\" IEEE Transactions on Computers (TC), Design of Integrated Circuits and Systems (TCAD), vol. 37, vol. 67, no. 7, pp. 1023-1038, Jul. 2018. no. 11, pp. 2790-2801, Nov. 2018. (Integrated with ACM/IEEE CODES+ISSS'18) 8. Chien-Chung Ho, Yu-Ming Chang, Yuan-Hao Chang, and Tei- Wei Kuo, \"SLC-Like Programming Scheme for MLC Flash 3. Chun-Feng Wu, Ming-Chang Yang, Yuan-Hao Chang, and Tei- Memory,\" ACM Transactions on Storage (TOS), vol. 14, no. 1, Wei Kuo, \"Hot-Spot Suppression for Resource-Constrained pp. 11:1-11:26, Mar. 2018. Image Recognition Devices with Non-Volatile Memory,\" IEEE Transactions on Computer-Aided Design of Integrated Circuits 9. Shuo-Han Chen, Tseng-Yi Chen, Yuan-Hao Chang, Hsin-Wen and Systems (TCAD), vol. 37, no. 11, pp. 2567-2577, Nov. 2018. Wei, and Wei-Kuan Shih, \"UnistorFS: A Union Storage File (Integrated with ACM/IEEE EMSOFT'18) System Design for Resource Sharing between Memory and Storage on Persistent RAM based Systems,\" ACM Transactions 4. Tseng-Yi Chen, Yuan-Hao Chang, Yuan-Hung Kuan, Ming-Chang on Storage (TOS), vol. 14, no. 1, pp. 3:1-3:22, Feb. 2018. Yang, Yu-Ming Chang, and Pi-Cheng Hsiu, \"Enhancing Flash Memory Reliability by Jointly Considering Write-back Pattern 10. Chun-Feng Wu, Ming-Chang Yang, and Yuan-Hao Chang, and Block Endurance,\" ACM Transactions on Design Automation \"Improving Runtime Performance of Deduplication System of Electronic Systems (TODAES), vol. 23, no. 5, pp. 64:1-64:24, with Host-Managed SMR Storage Drives,\" ACM/IEEE Design Aug. 2018. Automation Conference (DAC), San Francisco, USA, Jun. 24-28, 2018. (Top Conference) 5. Shuo-Han Chen, Yuan-Hao Chang, Yu-Pei Liang, Hsin-Wen Wei, and Wei-Kuan Shih, \"An Erase Efficiency Boosting Strategy for 3D Charge Trap NAND Flash,\" IEEE Transactions on Computers (TC), vol. 67, no. 9, pp. 1246-1258, Sep. 2018. 168

Associate Research Fellow 莊庭瑞 研 究 Tyng-Ruey Chuang 人 員 Ph.D., Computer Science, New York University, United States Faculty T +886 2-2788-3799 ext.1613 E [email protected] F +886 2-2782-4814 W www.iis.sinica.edu.tw/~trc/ ・ Associate Research Fellow, Institute of Information Science (2001-present), Research Center for Information Technology Innovation (2008-present), and Research Center for Humanities and Social Sciences (2014-present), Academia Sinica ・ Associate Professor (Adjunct), Department of Information Management, National Taiwan University (2008-2014) ・ Fellow, Berkman Center for Internet and Society, Harvard University (2011-2012) ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica (1994-2001) ・ Guest Researcher, Department of Computing Science, Chalmers University of Technology (1993) Research Description My research interests include functional programming, geospatial informatics, collaborative data projects and policies, and topics in digital humanities. We propose a parametric content model for structural documents. The model provides a basis for typeful XML programming in ML, and leads to modular and validated document transformational programs. We study the temporal properties of OpenStreetMap datasets to better understand the unevenness in user participation and data quality of volunteered geographic information. We re-purpose the OpenStreetMap technical infrastructure so as to bring out new representations from old maps. We design a communal data work ow for TaiRON (https://roadkill.tw/) in which thousands of participants contribute roadkill observation records. Datasets from this collaborative e ort have been used in designing new measures to reduce roadkill, and in monitoring unusual animal deaths in Taiwan. The project received a 2019 National Agricultural Science Award in the Sustainable Environment category. We initiate an archive (http://public.318.io/) of artifacts, images, and videos from the 2014 Sun ower Movement. The entire collection had been transferred to the National Museum of Taiwan History, and was featured in a special exhibition on Social Movements in Post-War Taiwan. We build depositar (https://data.depositar.io/), an open repository for research data. We are working with the Ministry of Science and Technology of Taiwan to develop research data management policies and guidelines. I am a member of the advisory committee of Academia Historia of Taiwan (2019-2020). I serve in the Committee on Data (CODATA) of the International Science Council as an elected member of its executive committee (2018-2020). I was the project lead of Creative Commons Taiwan for 15 years before its transition to a community project in 2018. Publications 1. Tyng-Ruey Chuang, Cheng-Jen Lee, Chia-Hsun Wang, and Yu- 6. Dong-Po Deng, Tyng-Ruey Chuang, Kwang-Tsao Shao, Guan- Brochure 2020 Huang Wang. Experience in Moving Toward An Open Repository Shuo Mai, Te-En Lin, Rob Lemmens, Cheng-Hsin Hsu, Hsu- For All. In Open Repositories 2020. Stellenbosch, South Africa, Hong Lin, and Menno-Jan Kraak. Using social media for May 2020. (Accepted) collaborative species identification and occurrence: issues, methods, and tools. In 1st ACM SIGSPATIAL International 2. Tyng-Ruey Chuang. Remembrance of contemporary events: Workshop on Crowdsourced and Volunteered Geographic On setting up the Sunflower Movement Archive. In Digital Information, pp.22-29. Redondo Beach, CA, USA. November 6, Scholarship in the Humanities, Volume 34, Issue Supplement 1, 2012. pp. i36-i45, December 2019. 7. Tyng-Ruey Chuang and Hui-Yin Wu. Structure-conforming XML 3. Tyng-Ruey Chuang, Chih-Chuan Hsu, and Huang-Sin Syu. document transformation based on graph homomorphism. In Maps Re-imagined: Digital, Informational, and Perceptional 2012 ACM Symposium on Document Engineering, pp. 99-102. Experimentations in Progress. In Digital Humanities 2019. Paris, France, September 2012. Utrecht, the Netherlands, July 2019. 8. Tyng-Ruey Chuang and Max Schaefer. Status report: Layered 4. Tyng-Ruey Chuang, Jheng-Peng Huang, Hsin-Huei Lee, Kae- streaming XML processing with modules. In 2007 ACM An Liu, and Huang-Sin Syu. Assisted journey recollections SIGPLAN Workshop on ML , pp. 53-58. Freiburg, Germany, from photo streams. In 24th ACM SIGSPATIAL International October 2007. Conference on Advances in Geographic Information Systems. Burlingame, CA, USA, November 2016. 9. Tyng-Ruey Chuang and Jan-Li Lin. On modular transformation of structural content. In 2004 ACM Symposium on Document 5. Tyng-Ruey Chuang, Dong-Po Deng, Chun-Chen Hsu and Rob Engineering, pp. 201-210. Milwaukee, WI, USA, October 2004. Lemmens. The one and many maps: Participatory and temporal diversities in OpenStreetMap. In 2 nd ACM SIGSPATIAL 10. Tyng-Ruey Chuang. Generic validation of structural content International Workshop on Crowdsourced and Volunteered with parametric modules. In 2001 International Conference on Geographic Information, pp. 79-86. Orlando, FL, USA, Functional Programming, pp. 98-101. Florence, Italy, September November 2013. 2001. 169

究研 人 Research Fellow 員 陳伶志 Ling-Jyh Chen Faculty Ph.D., Computer Science, University of California at Los Angeles, United States T +886-2-2788-3799 ext. 1702 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/cclljj ・ Director (2018-present), Department of Information Technology Services, Academia Sinica ・ Assistant Research Fellow (2005), Associate Research Fellow (2011), Research Fellow (2017-present), Institute of Information Science, Academia Sinica Research Description My research interests lie in the area of networked sensing systems and applications. The primary objectives of my research are 1) to investigate theoretical models of real-world systems; 2) to conduct real world deployment to verify theoretical models; and 3) to combine theoretical models and system deployment to solve real world problems. Speci cally, we investigate Internet of Things systems and develop a large-scale system, called AirBox, for participatory PM2.5 monitoring. The project engages citizens to participate in environmental sensing and enables them to make low-cost PM2.5 sensing devices on their own. It also facilitates PM2.5 monitoring at a ner spatio-temporal granularity and enriches environmental data analysis by making all measurement data freely available to everyone. Till 2020, we have deployed more than 15,000 devices in 58 countries, and we have developed a set of algorithms for device ranking, emission source detection, anomaly detection, PM2.5 forecast, and clean air routing applications. Based on our research results, we have been collaborating with the government agencies on smart governance, smart inspection, and the related issues. My ongoing research focuses on spatio-temporal data analysis of IoT systems and its applications. We intend to apply our research results to other real-world networked sensing systems, such as participatory sensing for urban pro ling, environmental monitoring, and wearable sensing and computing. Moreover, we wish to employ advanced arti cial intelligence techniques to increase the intelligence of networked sensing systems, and we will incorporate our research results with emerging social computing systems as a whole to facilitate cyber-physical socially networked systems in the future. Publications 1. Jiayu Li, Huang Zhang, Chun-Ying Chao, Chih-Hsiang Chien, 6. Guowen Huang, Ling-Jyh Chen, Wen-Han Hwang, ShengLi Chang-Yu Wu, Cyuan Heng Luo, Ling-Jyh Chen, and Pratim Tzeng, and Hsin-Cheng Huang. Real-Time PM2.5 Mapping and Biswas. Integrating Low-cost Air Quality Sensor Networks Anomaly Detection from AirBoxes in Taiwan. Environmetrics, with Fixed and Satellite Monitoring Systems to Study Ground- volume 29, issue 8, e2537, December, 2018. level PM2.5 Atmospheric Environment. Elsevier Atmospheric Environment, volume 223, pages 117293, February, 2020. 7. Yi-Bing Lin, Ying-Ju Shih, Hung-Chun Tseng, and Ling-Jyh Chen. LWA Rate Adaption by Enhanced Event - Triggered 2. Nai-Cih Liou, Cyuan-Heng Luo, Sachit Mahajan, and Ling-Jyh Reporting. IEEE Transactions on Vehicular Technology, volume Chen. Why Is Short-Time PM2.5 Forecast Difficult? The Effects 67, issue 11, pp. 10950-10959, November, 2018. of Sudden Events. IEEE Access Journal, volume 8, pp. 12662 - 12674, December, 2019. 8. Sachit Mahajan, Hao-Min Liu, Tzu-Chieh Tsai, and Ling-Jyh Chen. Improving the Accuracy and Efficiency of PM2.5 Forecast 3. Sachit Mahajan, Yu-Siou Tang, Dong-Yi Wu, Tzu-Chieh Tsai, and Service Using Cluster-based Hybrid Neural Network Model. Ling-Jyh Chen. CAR: The Clean Air Routing Algorithm for Path IEEE Access Journal, volume 6, pp. 19193-19204, March, 2018. Navigation with Minimal PM2.5 Exposure on the Move. IEEE Access Journal, volume 7, pp. 147373 - 147382, October, 2019. 9. Ling-Jyh Chen, Yao-Hua Ho, Hsin-Hung Hsieh, Shih-Ting Huang, Hu-Cheng Lee, and Sachit Mahajan. ADF: an Anomaly 4. Yi-Bing Lin, Hung-Chun Tseng, Li-Chang Wang, and Ling-Jyh Detection Framework for Large-scale PM2.5 Sensing Systems. Chen. Performance of Splitting LTE-WLAN Aggregation. ACM/ IEEE Internet of Things Journal, volume 5, issue 2, pp. 559-570, Springer Mobile Networks and Applications, volume 24, issue 5, April, 2018. pp. 1587-1595, October, 2019. 10. Ling-Jyh Chen, Yao-Hua Ho, Hu-Cheng Lee, Hsuan-Cho Wu, 5. Yi-Bing Lin, Hung-Chun Tseng, Yun-Wei Lin, and Ling-Jyh Hao-Min Liu, Hsin-Hung Hsieh, Yu-Te Huang, and Shih-Chun Chen. NB-IoTtalk: A Service Platform for Fast Development of Candice Lung. An Open Framework for Participatory PM2.5 NB-IoT Applications. IEEE Internet of Things Journal, volume 6, Monitoring in Smart Cities. IEEE Access Journal, volume 5, pp. issue 1, pp. 928-939, February, 2019. 14441-14454, July, 2017. 170

Research Fellow 陳孟彰 研 究 Meng Chang Chen 人 員 Ph.D., Computer Science, University of California at Los Angeles, United States Faculty T +886-2-2788-3799 ext. 1802 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/mcc ・ Deputy Director, Institute of Information Science, Academia Sinica (1999-2002, 2008- 2010) ・ Principal investigator, Patent and Technology Exchange Group, National Telecom Project O ce, (2001-2003) ・ Member of Technical Sta , Bell Labs, AT&T, (1989-1992) Research Description My research interests are in computer and network software system, and data and knowledge engineering, and various problems within the areas. In the 2000s, I worked on text mining problem, especially in summarization and story generation from a collection of articles (e.g., query return from Google). Simultaneously, I also worked on the wireless networking, including multi-hop mesh transmission, 5G small cell ultra-dense network, and network mobility on high speed vehicle. Currently, I work on two issues, deep learning for PM2.5 prediction, and malware analysis. First, we proposed the composite neural network framework, which proves with high probability that a composite neural network performs better than any of its pre-trained component, regardless of topology. The PM2.5 prediction is a great challenge that requires both deep domain knowledge and deep learning skills. We, based on composite neural network framework, considered many highly in uencing factors (e.g., remote transportation, time-e ect) and developed needed theories (e.g., extreme case distribution, step-function-like loss function) in order to obtain high quality ne-grained 72 hours prediction. For malware analysis, rst, we built a hardware-assisted VMI (virtual machine introspection) mechanism from a software stack containing virtual machine, hypervisor, and QMEU and run captured malware in this control environment. Our malware analysis includes both static and dynamic analyses. The dynamic analysis uses the execution trace collected from the rst step to further investigate the API/system calls and resources used by the malware. The static analysis looks into the malware program to perform statistics on API calls and generates call graph and extract the low frequency calls. Later on, we considered all the extractions as features and applied the composite neural network framework to build an e cient and high accuracy deep learning apparatus for various malware analysis, such as malware family classi cation. Currently, we use Mitre Att&ck repository to extract Malware attack knowledge to identify the attack path of a malware. 1. \"Composite Neural Network: Theory and Application to Publications Brochure 2020 PM2.5 Prediction\", Ming-Chuan Yang and Meng Chang Chen, arXiv:1910.09739, Oct., 2019. 6. \"A Two-Stage Link Scheduling Scheme for Variable-Bit-Rate Traffic Flows in Wireless Mesh Networks\", Yung-Cheng Tu, 2. \"Hardware-Assisted MMU Redirection for In-guest Monitoring Meng Chang Chen and Yeali S. Sun, IEEE Transactions on and API Profiling\", Mike Hsiao, Yeali Sun, Meng Chang Chen, Wireless Communications, November 2014. accepted by IEEE Transactions on Information Forensics & Security. 7. \"Coding-Aware Peer-to-Peer Data Repair in Multi-Rate Wireless Networks - A Game Theoretic Analysis\", Hsiao-Chen Lu, 3. \"NASH: Navigation-Assisted Seamless Handover Scheme for Wanjiun Liao, Meng Chang Chen, and Musaed A. Alhussein, Smart Car in Ultra-Dense Networks\", Ming-Chin Chuang, Meng IEEE Journal on Selected Areas in Communications, Special Chang Chen, IEEE Transactions on Vehicular Technology , Issue on Emerging Technologies in Communications, September February 2018. 2013. 4. \"Slow-Paced Persistent Network Attacks Analysis and Detection 8. \"Protocol and Architecture Supports for Network Mobility with Using Spectrum Analysis\", Li Ming Chen, Shun-Wen Hsiao, QoS-Handover for High-Velocity Vehicles\", Cheng-Wei Lee, Meng Chang Chen, and Wanjiun Liao, IEEE Systems Journal, Yeali Sun and Meng Chang Chen, Wireless Networks. July 2013. December 2016. 9. \"TSCAN: A Content Anatomy Approach to Temporal Topic 5. \"Seamless Handover for High-Speed Trains Using Femtocell- Summarization\", Chien Chin Chen and Meng Chang Chen, IEEE based Multiple Egress Network Interfaces\", Cheng-Wei Lee, Transactions on Knowledge and Data Engineering, January 2012. Ming-Chin Chuang, Meng Chang Chen and Yeali S. Sun, IEEE Transactions on Wireless Communications, December 2014. 10. \"Using Incremental PLSI for Threshold Resilient Online Event Analysis\", Tzu-chuan Chou and Meng Chang Chen, IEEE Transactions on Knowledge and Data Engineering, March 2008. 171

究研 人 Research Fellow 員 陳郁方 Yu-Fang Chen Faculty Ph.D., Information Management, National Taiwan University, Taiwan T +886-2-2788-3799 ext. 1514 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/yfc ・ Research Fellow, IIS, Academia Sinica (2018-present) ・ Professor, IM, National Taiwan University (2019) ・ Professor, MIS, National Taipei University (2019-present) ・ Associate Research Fellow, IIS, Academia Sinica (2014-2018) ・ Adjunct Associate Professor, MIS, National Taipei University (2014-2019) ・ Adjunct Assistant Professor, IM, National Taiwan University (2010-2014) ・ Assistant Research Fellow, IIS, Academia Sinica (2009-2014) ・ PostDoc, Uppsala University (2009) ・ EATCS (European Association for Theoretical Computer Science) award for best theoretical paper at ETAPS 2010 Research Description My primary interest is the development of principled methods to ensure the correctness and security of computer programs. I am best known for my works in the application of algorithmic learning algorithms to automate formal verification and the design of efficient algorithms for nite state automata operations. In recent years, I am shifting my research directions to the analysis of real-world programs, in particular, the veri cation and testing of web program security. Web program security is a crucial building block of our digital infrastructure. Among other means to ensure cybersecurity, there is an apparent demand in approaches for automatic web program analysis. String constraint solver is the engine of modern web program testers and veri ers. There has been a substantial amount of research in recent years on the development of solvers for string constraints. This has been motivated by numerous application areas such as web security enhancement. Together with my cooperators from Europe, our team has being working on the problem of string constraint solving since 2014. We have obtained a series of success in this direction. For example, our string constraint solver Trau [4,5,6] is among the most efficient implementations in the world. We proposed the first string constraint solving procedure that is able to generate Craig interpolant [1,2], which is essential in the invariant generation for software model checking. In May 2019, the rst edition of Meeting on String Constraints and Applications (MOSCA 2019) was held in Bertinoro, Italy. In one week, 43 experts from industry and academia interested in this topic are invited to present their work and exchange ideas. The participants including researchers from Microsoft, Amazon, and NASA. I am one of the invitees and will be the organizer of the next edition of MOSCA. I gave two invited tutorials on this topic at international conferences: CONCUR 2018 (3hrs), SETTA 2019 (2hrs). Our research results are published in CAV 2014, CAV 2015, PLDI 2017, and FMCAD 2018, and PLDI 2020. Those are most inferential venues for formal veri cation and programming language researches. Publications 6. Parosh Aziz Abdulla, Mohamed Faouzi Atig, Yu-Fang Chen, Phi-Diep Bui, Julian Dolby, Petr Janku, Hsin-Hung Lin, Lukas 1. Parosh Aziz Abdulla, Mohamed Faouzi Atig, Yu-Fang Chen, Holik, Wei-Cheng Wu \"Efficient Handling of String-Number Lukás Holík, Ahmed Rezine, Philipp Rümmer, Jari Stenman, Conversion\", PLDI 2020. \"String Constraints for Verification\", CAV 2014. 7. Yu-Fang Chen, Ondrej Lengal, Tony Tan, Zhilin Wu, \"Register 2. Parosh A. Abdulla, Mohamed Faouzi Atig, Yu-Fang Chen, Lukás automata with linear arithmetic\", LICS 2017. Holík, Ahmed Rezine, Philipp Rümmer, Jari Stenman, \"Norn: An SMT Solver for String Constraints\", CAV 2015. 8. Yu-Fang Chen, Lei Song, Zhilin Wu, \"The Commutativity Problem of the MapReduce Framework: A Transducer-Based 3. Fang Yu, Ching-Yuan Shueh, Chun-Han Lin, Yu-Fang Chen, Approach\", CAV 2016. Bow-Yaw Wang, Tevfik Bultan, \"Optimal Sanitization Synthesis for Web Application Vulnerability Repair\", ISSTA 2016. 9. Yu-Fang Chen, Matthias Heizmann, Ondrej Lengal, Yong Li, Ming-Hsien Tsai, Andrea Turrini, Lijun Zhang, \"Advanced 4. Parosh Aziz Abdulla, Mohamed Faouzi Atig, Phi-Diep Bui, Automata-based Algorithms for Program Termination Checking\", Yu-Fang Chen, Lukáš Holík, Ahmed Rezine, Philipp Rümmer, PLDI 2018. \"Flatten and Conquer (A Framework for Efficient Analysis of String Constraints)\", PLDI 2017. 10. Yu-Fang Chen, Chiao Hsieh, Ondrej Lengál, Tsung-Ju Lii, Ming- Hsien Tsai, Bow-Yaw Wang, Farn Wang, \"PAC Learning-based 5. Parosh Aziz Abdulla, Mohamed Faouzi Atig, Yu-Fang Chen, Bui Verification and Model Synthesis\", ICSE 2016. Phi Diep, Lukás Holík, Ahmed Rezine, Philipp Rümmer, \"Trau: SMT solver for string constraints\", FMCAD 2018. 172

Research Fellow 陳祝嵩 研 究 Chu-Song Chen 人 員 Ph.D., Computer Science and Information Engineering, Faculty National Taiwan University, Taiwan T +886-2-2788-3799 ext. 1310 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/song ・ Governing Board Member, IPPR Society, Taiwan (2015-present) ・ Adjunct Professor, GINM, National Taiwan University (2009-present) ・ Deputy Director, CITI, Academia Sinica (2008-2015) ・ Secretary-General, IPPR Society, Taiwan (2007-2008) ・ Associate Research Fellow, IIS, Academia Sinica (2003-2008) ・ Adjunct Associate Professor, NTPU, Dept. of CSIE (2004-2005) ・ Joint Appointment Assistant Professor, NTNU, Dept. of GAC (2001-2004) ・ Assistant Research Fellow, IIS, Academia Sinica (1999-2003) Research Description Dr. Chu-Song Chen received a Ph.D degree in 1996 from CSIE, National Taiwan University. He is a research fellow/professor of IIS and a joint- appointment research fellow/Professor of CITI, Academia Sinica. He also serves as an adjunct professor of GINM, National Taiwan University. His research interests include deep learning, pattern recognition, computer vision, and multimedia. He is on the governing board of the Image Processing and Pattern Recognition (IPPR) Society, which is a regional society of International Association of Pattern Recognition (IAPR). He is also with the Most Joint Research Center for AI Technology and All Vista Healthcare. Currently, he serves as an associate editor of the journals Pattern Recognition (Elsevier) and Machine Vision & Applications (Springer). Dr. Chen devotes to deep learning researches in these years. In this eld, he has several publications on top conferences (such as CVPR, ICCV, ACM MM, IJCAI, NeurIPS) and journals (IEEE TPAMI, TNNLS). His works of deep learning of binary features for e cient retrieval (CVPRW15, TPAMI18) are leading studies on hash function learning via deep networks, which have been cited for more than 550 times according to google scholar. His team won the champion of National Intelligent-Manufacture Big-Data (IMBD) analysis challenge in 2019. His recent studies focus on merging and lifelong-learning of deep models, medical image analysis, AI in emergency medicine, and 3D environment exploration and reconstruction. 1. Huei-Fang Yang, Kevin Lin, Ting-Yen Chen, and Chu-Song Publications Chen, \"Cross-batch Reference Learning for Deep Retrieval,\" to appear in IEEE Trans. on Neural Networks and Learning 6. Kuang-Yu Chang, Kung-Hung Lu, and Chu-Song Chen, \"Aesthetic Systems . Critiques Generation for Photos,\" ICCV 2017. 2. Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung 7. Kuan-Wen Chen, Chun-Hsin Wang, Xiao Wei, Qiao Liang, Chu- Chen, Yi-Ming Chan, and Chu-Song Chen, \"Compacting, Picking Song Chen, Ming-Hsuan Yang, and Yi-Ping Hung, \"Vision-Based and Growing for Unforgetting Continual Learning,\" NeurIPS Positioning for Internet-of-Vehicles,\" IEEE Trans. on Intelligent 2019 . Transportation Systems, volume 18, number 2, February 2017. 3. Kevin Lin, Jiwen Lu, Chu-Song Chen, Jie Zhou, and Ming- 8. Huei-Fang Yang, Kevin Lin, and Chu-Song Chen, \"Cross-batch Ting Sun, \"Unsupervised Deep Learning of Compact Binary Reference Learning for Deep Classification and Retrieval,\" ACM Descriptors,\" IEEE Trans. on Pattern Analysis and Machine MM 2016 (long paper). Intelligence, volume 41, number 6, June 2019. 9. Kevin Lin, Jiwen Lu, Chu-Song Chen, and Jie Zhou, \"Learning 4. Yi-Min Chou, Yi-Ming Chan, Jia-Hong Lee, Chih-Yi Chiu, Chu- Compact Binary Descriptors with Unsupervised Deep Neural Song Chen, \"Unifying and Merging Well-trained Deep Neural Networks,\" CVPR 2016. Networks for Inference Stage,\" IJCAI 2018. 10. Kevin Lin, Huei-Fang Yang, Jen-Hao Hsiao, and Chu-Song Chen, 5. Huei-Fang Yang, Kevin Lin, and Chu-Song Chen, \"Supervised \"Deep Learning of Binary Hash Codes for Fast Image Retrieval,\" Learning of Semantics-Preserving Hash via Deep Convolutional CVPR Workshop on DeepVision 2015. Neural Networks,\" IEEE Trans. on Pattern Analysis and Machine Intelligence, volume 40, number 2, February 2018. Brochure 2020 173

究研 人 Research Fellow 員 黃文良 Wen-Liang Hwang Faculty Ph.D., Computer Science, New York Univeristy, United States T +886-2-2788-3799 ext. 1609 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/whwang ・ Research Fellow, Institute of Information Science, Academia Sinica, Taiwan (2005/1-present) ・ Associate Research Fellow, Institute of Information Science, Academia Sinica, Taiwan (1999/1-2005/1) ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica, Taiwan (1995/1-1999/1) ・ Associate Post Doctoral Researcher, Department of Mathematics, University of California, Irvine, United States (1993/1-1994/1) ・ Research Assistant, Department of Computer Science, New York University, United States (1990/1-1993/1) ・ Ph.D., Computer Science, New York University, United States (1989/1-1993/6) ・ M.S., Electrical Engineering, Polytechnic University, United States (1986/9-1989/1) ・ B.S., Nuclear Engineering, National Tsing Hua University, Taiwan (1977/9-1981/7) Research Description My research interests are deep neural network analysis and optimization. In deep neural network analysis, I invent the un-rectifying technique to derive the explicit representation of a network with point-wise piecewise linear activation functions. By now, I focus on using the technique to derive solutions to problems relevant to learning deep feed-forward networks, invertible deep networks, and networks containing loops. The inverse problems can be treated by the regularization or by the forward inference through a non-linear network. To study the invertible deep networks is motivated from observing inverse problem can also be solved by backward inference if the problem can be represented as an invertible network. In biology, the connectivity of neurons comprises of loops. To discover what information is encoded along the time via loops motivates my study of the dynamic behaviors of loops. I am also attracted by optimization methods. In research, I focus on realizing the idea of introducing auxiliary operators (functions) to help solving optimization problems. So far, I do not fully understand the feasibility of the idea rather than exercising it in cases by cases basis. In one case, I demonstrate operators can be constructed and applied to separation of a super-position of di ering types of signals from observations of one channel or multiple channels. In my previous researches, I study instantaneous frequency and singularity detection and characterization methods via wavelets. My representative shows that both can be simultaneously detected and characterized using complex-valued wavelets. My representative in video coding is the formulation of the scalable coding as a multi-objective optimization problem and identi es some interesting Pareto points for performance measurements. This result provides a way to understand the intrinsic di culty of performance evaluation of scaling coding and may inspire new performance evaluation methods. Publications 1. Wen-Liang Hwang, Andreas Heinecke, \"Un-rectifying Non-linear 6. Xiyuan Hu, Silong Peng, and Wen-Liang Hwang, \"EMD Networks for Signal Representation,\" IEEE Transactions on Revisited: A New Understanding of the Envelope and Resolving Signal Processing, volume 68, pages 196-210, December 2019. the Mode-Mixing Problem in AM-FM Signals,\" IEEE Transactions on Signal Processing, volume 60, number 3, pages 2. Wen-Liang Hwang, Chia-Chen Lee, and Guan-Ju Peng, \"Multi- 1075-1086, March 2012. Objective Optimization and Characterization of Pareto Points for Scalable Coding,\" IEEE Transactions on Circuits and Systems for 7. Silong Peng and Wen-Liang Hwang, \"Null Space Pursuit: An Video Technology, volume 29, number 7, pages 2096 - 2111, July Operator-based Approach to Adaptive Signal Separation,\" IEEE 2019. Transactions on Signal Processing, volume 58, pages 2475-2483, May 2010. 3. Wen-Liang Hwang, Ping-Tzan Huang, Bo-Chen Kung, Jinn Ho, and Tai-Lang Jong, \"Frame-based Sparse Analysis and Synthesis 8. Chun-Liang Tu, Wen-Liang Hwang, and Jinn Ho, \"Analysis of Signal Representations and Parseval K-SVD,\" IEEE Transactions Singularities from Modulous Maxima of Complex Wavelets,\" on Signal Processing, volume 67, number 12, pages 3330 - 3343, IEEE Transactions on Information Theory, volume 51, number 3, June 2019. pages 1049-1062, March 2005. 4. Wen-Liang Hwang, Keng-Shih Lu, and Jinn Ho, \"Constrained 9. Wen-Liang Hwang and Stephane Mallat, \"Singularity Detection Null Space Component Analysis for Semi-Blind Source and Processing with Wavelets,\" IEEE Transactions on Information Separation Problem,\" IEEE Transactions on Neural Networks and Theory, volume 32, number 2, March 1992. Learning Systems, volume 29, pages 377-391, November 2016. 10. Rene Carmona, Wen-Liang Hwang, and Bruno Torresani, 5. Jinn Ho, Wen-Liang Hwang, \"Wavelet Bayesian Network Image \"Practical Time-Frequency Analysis,\" Academic Press, 1998. Denoising,\" IEEE Transactions on Image Processing, volume 22, number 4, pages 1277 - 1290, April 2013. 174

Research Fellow 楊柏因 研 究 Bo-Yin Yang 人 員 Ph.D., Mathematics, Massachusetts Institute of Technology, United States Faculty T +886-2-2788-3799 ext. 1731 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/byyang ・ B.S. Mathematics, National Taiwan University (1987) ・ Ph.D. Mathematics, Massachusetts Institute of Technology (1991) ・ Associate Professor of Mathematics, Tamkang University, (1992-2006) ・ Associate Research Fellow, IIS, Academia Sinica, (2006-2011), ・ Research Fellow, IIS, Academia Sinica, (2011-present) ・ Joint Appointed Research Fellow, CITI, Academia (2011-present) ・ Career Advancement Award, Academia Sinica (2010-2014) ・ Sinica Investigator Award, Academia Sinica (2015-2019, 2020-2024) Research Description My research is mainly in applied cryptography and e cient implementations of cryptography and cryptanalysis. Our team is internationally renowned particularly the study of post-quantum cryptography and cryptographic implementation especially on specialist platforms. We entered the the U.S. National Institute for Standards and Technology (NIST) competition for new the second round. We also spend time doing postquantum crypto standards and have a candidate in high assurance crypto software, meaning we try to formally verify cryptographic subroutines as correct. There is always a tradeo of security against speed. E cient implementation of cryptography is therefore extremely important in that only fast enough applications will get used. One unfortunate di erence when programming for crypto applications is that compiling C usually yields very suboptimal code because cryptographers are not the intended clientele of vendors. Another unique aspect of cryptography is that to conform to the security model data ow from secrets to observables must be avoided. So we can't read with a secret index from a table, and can't branch depending on secret data. Pragmatically, this also means no bugs. Correctness is as important as speed. We have contributed to high-speed high-security Ed25519 elliptic curve cryptosystem, which is recently incorporated into the new FIPS 186- 5 standards. Our code is also found in some NIST second round candidates. Publications 1. W.-L. Huang, J.-P. Chen, and B.-Y. Yang, Power Analysis on 7. D. J. Bernstein and B.-Y. Yang, Asymptotically faster quantum Brochure 2020 NTRU Prime, IACR Transactions on Cryptographic Hardware algorithms to solve multivariate quadratic equations, PQCrypto and Embedded Systems (TCHES), 2020(1), pp. 123-151. 2018 , LNCS 10786, pp. 487-506. 2. Y.-F. Fu, J. Liu, X. Shi, M.-H. Tsai, B.-Y. Wang, and B.-Y. 8. R. Niederhagen, K.-C. Ning and B.-Y. Yang, Implementing Joux- Yang, Signed Cryptographic Program Verification with Typed Vitse's Crossbred Algorithm for Solving MQ Systems on GPUs, CryptoLine, ACM CCS 2019. PQCrypto 2018, ibid. pp. 121-141. 3. J. Liu, X. Shi, M.-H. Tsai, B.-Y. Wang, and B.-Y. Yang, Verifying 9. M.-S. Chen, W.-D. Li, B.-Y. Peng, B.-Y. Yang, and C.-M. Arithmetic in Cryptographic C Programs, ASE 2019. Cheng, Implementing 128-bit Secure MPKC Signatures, IEICE Transactions vol. E101-A(2018) No. 3, pp. 553-569. 4. D. J. Bernstein and B.-Y. Yang, Fast constant-time gcd computation and modular inversion. IACR Transactions on 10. M.-H. Tsai, B.-Y. Wang, and B.-Y. Yang Certified Verification Cryptographic Hardware and Embedded Systems (TCHES), of Algebraic Properties on Low-Level Mathematical Constructs 2019(3), pp. 340-398. in Cryptographic Programs, proc. ACM CCS 2017 (24th ACM Conference on Computer and Communications Security, Dallas, 5. A. Polyakov, M.-H. Tsai, B.-Y. Wang, and B.-Y. Yang, Verifying TX, USA, Oct. 30-Nov. 3), pp. 1973-1987. Arithmetic Assembly Programs in Cryptographic Primitives, Invited Talk and Paper, CONCUR 2018: Leibniz International 11. A. Petzoldt, M.-S. Chen, B.-Y. Yang, C. Tao, J. Ding: Design Proceedings in Informatics 118, pp. 4:1-4:16. Principles for HFEv- Based Multivariate Signature Schemes, Asiacrypt 2015, LNCS 9452, pp. 311-334. 6. W.-D. Li, M.-S. Chen, P.-C. Kuo, C.-M. Cheng, and B.-Y. Yang, Frobenius Additive Fast Fourier Transform, Proc. ACM ISSAC 2018, pp. 1973-1987. 175

究研 人 Research Fellow 員 楊得年 De-Nian Yang Faculty Ph.D., Electrical Engineering, National Taiwan University, Taiwan T +86-2-2788-3799 ext. 1728 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/dnyang ・ Young Scholar Creativity Award, Foundation for Advancement of Outstanding Scholarship, Taiwan (2018) ・ Project for Excellent Junior Research Investigator, Ministry of Science and Technology, Taiwan (2012-2015, 2016-2018) ・ IEEE INFOCOM Best In-Session Presentation Award, USA (2016) ・ Junior Research Investigators Award, Academia Sinica, Taiwan (2015) ・ PAKDD Best Paper Running-Up Award, Vietnam (2015) ・ ACM CHI Best Paper Honorable Mention Award, Canada (2014) ・ IEEE GLOBECOM Best Paper Nominate, USA (2014) ・ Outstanding Youth Electrical Engineer Award, Chinese Institute of Electrical Engineering, Taiwan (2013) Research Description My research interests include network analysis and optimization for social networks and communications networks, from the perspective of graph theory, approximation algorithms, machine learning, and data mining. My research on social networks aims to address both theoretical rigor and practical novelty. Previous research results received various awards in IEEE INFOCOM, GLOBECOM, ICME, PAKDD, ACM CHI, and SIGGRAPH. For group analysis and optimization in social networks, we formulated new optimization and query processing problems, proved the NP-hardness and inapproximability, designed new algorithms with approximation guarantees, implemented them in real platforms (such as Facebook and Twitch), and transferred them to industry (such as Chunghwa Telecom for promotion with viral marketing in phone social networks). For group therapy for social network mental disorders (SNMDs), we were the rst team that studied SNMDs with machine learning and data mining techniques, aiming to actively identify SNMDs and support online intervention at an early stage. The research results were invited and presented in MSRA Faculty Summit in the session of \"AI and Psychology.\" For communication networks, we formulated new optimization problems with practically important SDN constraints, proved the NP-hardness and inapproximability, designed new algorithms with the tightest approximation ratios, implemented them in real platforms (HP SDN Switch and Floodlight SDN Controller), and transferred them to industry (such as Inventec for SDN controller and EstiNet for SDN network planning package). For multimedia networks, we optimized LTE-A resource allocations for virtual reality and multi-view videos. I served as the chair or co-chair in various committees of WWW, IEEE GLOBECOM, MDM, IEEE COMSOC Asia Paci c Board, INFORMS, and senior PC in AAAI and IJCAI. Publications 6. T.-C. Chang, Y. Shi, D.-N. Yang, and W.-T. Chen, \"Seed Selection and Social Coupon Allocation for Redemption Maximization in 1. S.-H. Ko, H.-C. Lai, H.-H. Shuai, W.-C. Lee, P. S. Yu, and D.-N. Online Social Networks,\" IEEE International Conference on Data Yang, \"Optimizing Item and Subgroup Configurations for Social- Engineering (IEEE ICDE), April 2019. Aware VR Shopping,\" International Conference on Very Large Data Bases (VLDB), August 2020. 7. H.-J. Hung, T.-Y. Ho, S.-Y. Lee, C.-Y. Yang, and D.-N. Yang, \"Relay Selection for Heterogeneous Cellular Networks with 2. C.-H. Wang, S.-H. Chiang, S.-H. Shen, D.-N. Yang, and W.- Renewable Green Energy Sources,\" IEEE Transactions on Mobile T. Chen, \"Multicast Traffic Engineering with Segment Trees in Computing, vol. 17, no. 3, pp. 661-674, March 2018. Software-Defined Networks,\" IEEE Conference on Computer Communications (IEEE INFOCOM), July 2020. 8. C.-Y. Shen, K. F. C. Parfait, D.-N. Yang, Y.-S. Chen, and W.-C. Lee, \"On Organizing Online Soirees with Live Multi-Streaming,\" 3. H.-J. Hung, W.-C. Lee, D.-N. Yang, C.-Y. Shen, Z. Lei, and S.-M. AAAI Conference on Artificial Intelligence (AAAI), February Chow, \"Efficient Algorithms towards Network Intervention,\" The 2018 (oral presentation, accepting rate = 11%). Web Conference (WWW), April 2020. 9. J.-T. Lee, D.-N. Yang, Y.-C. Chen, and W. Liao, \"Efficient Multi- 4. Y.-L. Chen, D.-N. Yang, C.-Y. Shen, W.-C. Lee, and M.-S. Chen, View 3D Video Multicast with Depth-Image-Based Rendering \"On Efficient Processing of Group and Subsequent Queries for in LTE-Advanced Networks with Carrier Aggregation,\" IEEE Social Activity Planning,\" IEEE Transactions on Knowledge Transactions on Mobile Computing , vol. 17, no. 1, pp. 85-98, and Data Engineering, vol. 31, no. 12, pp. 2364-2378, December January 2018. 2019. 10. C.-Y. Shen, L.-H. Huang, D.-N. Yang, H.-H. Shuai, W.-C. Lee, 5. S.-H. Ko, Y.-C. Lin, H.-C. Lai, W.-C. Lee, and D.-N. Yang, and M.-S. Chen, \"On Finding Socially Tenuous Groups for Online \"On VR Spatial Query for Dual Entangled Worlds,\" ACM Social Networks,\" ACM SIGKDD International Conference on International Conference on Information and Knowledge Knowledge Discovery and Data Mining (ACM KDD), August Management (ACM CIKM), November 2019. 2017 (oral presentation, accepting rate = 8.6%). 176

Research Fellow 葉彌妍 研 究 Mi-Yen Yeh 人 員 Ph.D., Electrical Engineering, National Taiwan University, Taiwan Faculty T +886-2-2788-3799 ext. 1412 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/miyen ・ Joint Assistant Professor (2014), Joint Associate Professor (2015), Joint Professor (2019-present), Dept. of Computer Science and Information Engineering, National Cheng Kung University ・ Associate Research Fellow (2014-2018), Assistant Research Fellow (2009-2014), Institute of Information Science, Academia Sinica Research Description My research mainly focuses on Data Mining, in particular on designing e ective and e cient algorithms to discover knowledge from Big Data, where we need to tackle the challenges bringing by the 4V characteristics: volume, velocity, veracity and variety. In the direction of tackling data volume and velocity, my research team and I have representative works such as considering how to e ciently search similar patterns among streaming time series in a central or distributed environment, how to design e cient algorithms for mining large-scale social network data, and how to accommodate the large-scale data over non-volatile memory such as ash while providing e cient and reliable tree index designs for data manipulation. In the direction of tackling data veracity and variety, we have representative works such as building a winning price model in the real-time bidding environment of online display advertisement when usually the historical winning price information is unobservable, building a recommender system while the social link information between users is either explicit or implicit, and dealing with the heterogeneous data in all the above applications at the same time. The rise of Big data era has empowered the deep learning techniques and the related AI applications. Our team will further explore the possibility of utilizing the deep learning models to the Big Data applications in consideration of those V-characteristics. 1. Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, and Publications Brochure 2020 Shou-De Lin, \"DeepRank: improving unsupervised node ranking via link discovery,\" Data Mining and Knowledge Discovery , 6. Su-Chen Lin, Mi-Yen Yeh, and Ming-Syan Chen, \"Non-overlapping volume 33, number 2, pages 474-498, March 2019. Subsequence Matching of Stream Synopses,\" IEEE Transactions on Knowledge and Data Engineering, volume 30, number 1, 2. Ming-Han Feng, Chin-Chi Hsu, Cheng-Te Li, Mi-Yen Yeh and pages 101-114, January 2018. Shou-De Lin, \"Multi-relational Network Embeddings with Relational Proximity and Node Attributes,\" The Web Conference 7. Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, and Shou- 2019 (WWW-2019), May 2019. De Lin, \"PRUNE: Preserving Proximity and Global Ranking for Node Embedding,\" The 31st Annual Conference on Neural 3. Chin-Chi Hsu, Mi-Yen Yeh, and Shou-De Lin, \"A General Information Processing Systems (NIPS-2017), December 2017. Framework for Implicit and Explicit Social Recommendation,\" IEEE Transactions on Knowledge and Data Engineering, volume 8. Chun-Yen Kuo, Mi-Yen Yeh, and Jian Pei, \"Principal Pattern Mining 30, number 12, pages 2228-2241, December 2018. on Graphs,\" The 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 4. Wush Chi-Hsuan Wu, Mi-Yen Yeh, and Ming-Syan Chen, (ASONAM-2017), July 2017. \"Deep Censored Learning of the Winning Price in the Real Time Bidding,\" 24th ACM SIGKDD International Conference on 9. Wush Chi-Hsuan Wu, Mi-Yen Yeh, and Ming-Syang Chen, Knowledge Discovery and Data Mining (KDD-2018), August \"Predicting Winning Price in Real Time Bidding with Censored 2018. Data,\" 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015), August 5. Chien-Wei Chang, Mi-Yen Yeh, and Kun-Ta Chuang, \"Node 2015. Reactivation Model to Intensify Influence on Network Targets,\" Knowledge and Information Systems, volume 54, number 3, 10. Hua-Wei Fang, Mi-Yen Yeh, Pei-Lun Suei, Tei-Wei Kuo, \"An pages 567-590, March 2018. Adaptive Endurance-Aware B+-Tree for Flash Memory Storage Systems,\" IEEE Transactions on Computers, volume 63, number 11, pages 2661-2673, November 2014. 177

究研 人 Research Fellow 員 廖純中 Churn-Jung Liau Faculty Ph.D., Computer Science and Information Engineering, National Taiwan University, Taiwan T +886-2-2788-3799 ext. 1713 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/liaucj/ ・ Associate Research Fellow, Institute of Information Science, Academia Sinica (1997-2004) ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica (1992-1997) ・ Ph.D., Computer Science and Information Engineering, National Taiwan University (1989- 1992) ・ M.S., Computer Science and Information Engineering, National Taiwan University (1985- 1987) ・ B.S., Computer Science and Information Engineering, National Taiwan University (1981-1985) ・ Associate Editor, International Journal of Approximate Reasoning (Elsevier) ・ Editorial Board Member, Fuzzy Sets and Systems (Elsevier) ・ Editorial Board Member, Transactions on Rough Sets (Springer-Verlag) Research Description My research interests include symbolic logic and its diverse applications. More speci cally, I am interested in the following subject areas: • epistemic/doxastic logic • deontic logic • belief revision and fusion • logic in arti cial intelligence • logic in privacy and security • reasoning about uncertainty • modal logic • possibilistic logic • rough set theory • many-valued logic Publications 1. C. J. Liau and I. P. Lin, Abstract minimality and circumscription, 7. T.-s. Hsu, C.J. Liau, and D.W. Wang, A logical framework for Artificial Intelligence, 54, 381-396, 1992. privacy-preserving social network publication, Journal of Applied Logic, 12(2): 151-174, 2014 2. C. J. Liau and I. P. Lin, Possibilistic reasoning--A mini-survey and uniform semantics, Artificial Intelligence, 88(1-2), 163-193, 8. T.F. Fan and C.J. Liau, Logical characterizations of regular 1996. equivalence in weighted social networks, Artificial Intelligence, 214:66-88, 2014 3. C.J. Liau, A logical analysis of the relationship between commitment and obligation, Journal of Logic, Language, and 9. C.P. Su, T.F. Fan, and C.J. Liau, Possibilistic justification logic: Information, 10(2), 237-261, 2001. Reasoning about justified uncertain beliefs, ACM Transactions on Computational Logic, 18(2): 15:1-15:21, 2017 4. C.J. Liau, Belief, information acquisition, and trust in multi agent systems - A modal logic formulation, Artificial Intelligence, 10. T.F. Fan and C.J. Liau, Reason-maintenance belief logic with 149(1), 31-60, 2003. uncertain information, ACM Transactions on Computational Logic, 21(1): 3:1-3:32, 2020 5. C.J. Liau, Belief fusion and revision: An overview based on epistemic logic semantics, Journal of Applied Non-Classical Logics, 14(3), 247-274, 2004, 6. C.J. Liau, A modal logic framework for multi-agent belief fusion, ACM Transactions on Computational Logic, 6(1), 124-174, 2005. 178

Associate Research Fellow 劉進興 研 究 Jing-Sin Liu 人 員 Ph.D., Electrical Engineering, National Taiwan University, Taiwan Faculty T +86-2-2788-3799 ext. 1813 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/liu ・ Associate Research Fellow, Institute of Information Science , Academia Sinica (1994 April-present) ・ Assistant Research Fellow, Institute of Information Science , Academia Sinica (1990 Aug.-1994 April) ・ IEEE Senior Member (2016 Feb.-present) Research Description Trajectory generation for unmanned vehicles in the presence of safety constraints and operating limits (such as bounds on velocity, acceleration, jerk and curvature) is challenging. Over these years, we have studied the path planning problems from the perspective: a high level trajectory planning based on a simple vehicle model that ignores high order e ect, while a low level path follower or the control design based on realistic, detailed, complicated dynamic model. Topics that we have studied include the smooth path planning problems using di erent path primitives for wheeled mobile robots and coverage path planning problems for unmanned aerial vehicles. With advances in computing power, optimal control can be used to formulate and solve for the increasingly more complex real-time optimal maneuvering problems of unmanned vehicles (such as UAVs) that require minimizing a cost functional. We study aggressive (time-optimal) state-to- state transfer driving maneuver (e.g. lane change), given the input and state constraints, boundary conditions, and the vehicle motion model, possibly with uncertainties. Numerical solvers for boundary value problems based on necessary optimality conditions derived from Pontryagin Maximum Principle are implemented. 1. Liu JS, Pan WH, Ku WY, Tsao YH, Chang YZ, 2016, Publications \"Simulation-based fast collision detection for scaled convex polyhedral objects in motion by exploiting analytical contact 6. Hsuan-Cheng Liao and Jing-Sin Liu,(2019)\"A Model-Based equations,\" Robotica, vol.34, no.1, pp.118-134, 2016. Reinforcement Learning Approach to Time-Optimal Control Problems,\" 32nd International Conference on Industrial, 2. Wu, K. L., Ho, T. J., Huang, S. A., Lin, K. H., Lin, Y. C., & Liu, Engineering & Other Applications of Applied Intelligent Systems J. S. (2016). Path Planning and Replanning for Mobile Robot (IEA/AIE-2019), Graz, Austria, July 2019. Navigation on 3D Terrain: An Approach Based on Geodesic. Mathematical Problems in Engineering, Volume 2016, Article ID 7. CY Lin and JS Liu, 2019, \"Reduce of DenseNet for UAV,\" 2539761, 12 pages http://dx.doi.org/10.1155/2016/2539761 International Workshop of Intelligent Artificial Life and Robotics Taiwan, Douliu YunLin, Taiwan, June 2019 (poster). Extended 3. Kuo, P. L., Wang, C. H., Chou, H. J., & Liu, J. S. (2018). A Real- version in Automation 2019, NTUST, Taipei, Taiwan, Nov. 2019. Time Hydrodynamic-Based Obstacle Avoidance System for Non- holonomic Mobile Robots with Curvature Constraints. Applied 8. WC Tung and JS Liu (2019),\"Genetic algorithm with modified Sciences, 8(11), 2144. operators for integrated traveling salesman problem and coverage path planning problem,\" 16th International Conference on Applied 4. Wu, C. S., Chiu, Z. Y., & Liu, J. S. (2018). Time-Optimal Computing, Cagliari, Italy, Nov. 2019. Code https://github.com/ Trajectory Planning along Parametric Polynomial Lane-Change WJTung/GA-TSPCPP Curves with Bounded Velocity and Acceleration: Simulations for a Unicycle Based on Numerical Integration. Modeling and 9. TW Hsu and JS Liu (2020),\"Design of smooth path based on Simulation in Engineering, Volume 2018, Article ID 9348907, 19 the conversion between eta3 spline and Bezier curve,\" 2020 pages American Control Conference, Denver, CO, USA, July, 2020. 5. Chou HJ and and Liu, J.-S. (2018) \"Numerical Study of Brochure 2020 Hamilton-Jacobi-Bellman Equation for Time-Optimal Trajectory Generation of Dubins Vehicle,\" 12th AIMS Conference on Dynamical Systems, Differential Equations and Applications, Taipei, Taiwan, July, 2018. 179

究研 人 Research Fellow 員 劉庭祿 Tyng-Luh Liu Faculty Ph.D., Computer Science, New York University, United States T +886-2-2788-3799 ext.1508 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/liutyng ・ Chief Scientist, Taiwan AI Labs (2019-present) ・ Academia Sinica Young Investigator Award (2006) ・ Visiting Scholar, School of Electrical and Computer Engineering, Cornell University (2013- 2014) Research Description My research has focused on computer vision and machine learning techniques that support real-life applications. I am most interested in understanding the fundamentals, and addressing critical issues in realizing vision (particularly, scene understanding) and natural language processing. Since the aforementioned applications rely heavily on the underlying imaging devices such as RGBD, 360-degree cameras, my research e orts also take this perspective into account in designing computer vision algorithms, ranging from low-level to high-level, to more appropriately exploit the available imaging information about the scene and its contents. In addition, generalizing conventional computer vision methods to deep learning approaches will continue to play a major role of my research themes. To expand my research scope, I collaborate with domain experts in designing e ective methods for medical imaging. Publications 1. Yen-Chi Hsu, Cheng-Yao Hong, Ming-Sui Lee, and Tyng-Luh 6. Kai-Yueh Chang, Tyng-Luh Liu, Hwann-Tzong Chen, and Shang- Liu, \"Query-Driven Multi-Instance Learning,\" Thirty-Fourth Hong Lai, \"Fusing Generic Objectness and Visual Saliency for AAAI Conference on Artificial Intelligence, February 2020. Salient Object Detection,\" International Conference on Computer (AAAI) Vision, Barcelona, Spain, November 2011. (ICCV) 2. Ting-I Hsieh, Yi-Chen Lo, Hwann-Tzong Chen, and Tyng-Luh 7. Yen-Yu Lin, Tyng-Luh Liu, and Chiou-Shann Fuh, \"Multiple Liu, \"One-Shot Object Detection with Co-Attention and Co- Kernel Learning for Dimensionality Reduction,\" IEEE Excitation,\" Thirty-third Conference on Neural Information Transactions on Pattern Analysis and Machine Intelligence, vol. Processing Systems, December 2019. (NeurIPS) 33, no. 6, pp. 1147-1160, 2011. (TPAMI) 3. Ding-Jie Chen, Songhao Jia, Yi-Chen Lo, Hwann-Tzong Chen, 8. Ye n - Yu L i n , Ty n g - L u h L i u , a n d C h i o u - S h a n n F u h , and Tyng-Luh Liu, \"See-through-Text Grouping for Referring \"Dimensionality Reduction for Data in Multiple Feature Image Segmentation,\" International Conference on Computer Representations,\" Twenty-second Conference on Neural Vision, October 2019. (ICCV) Information Processing Systems, December 2008. (NeurIPS) 4. Ding-Jie Chen, Jui-Ting Chien, Hwann-Tzong Chen, and Tyng- 9. Yen-Yu Lin, Tyng-Luh Liu, and Chiou-Shann Fuh, \"Local Luh Liu, \"Unsupervised Meta-learning of Figure-Ground Ensemble Kernel Learning for Object Category Recognition,\" Segmentation via Imitating Visual Effects,\" Thirty-Third AAAI IEEE Computer Society International Conference on Computer Conference on Artificial Intelligence, January 2019. (AAAI) Vision and Pattern Recognition, Minneapolis, MN, USA, June 2007. (CVPR) 5. Hsien-Tzu Cheng, Chun-Hung Chao, Jin-Dong Dong, Hao-Kai Wen, Tyng-Luh Liu, and Min Sun, \"Cube Padding for Weakly- 10. Hwann-Tzong Chen, Huang-Wei Chang, and Tyng-Luh Liu, Supervised Saliency Prediction in 360° Videos,\" IEEE Computer \"Local Discriminant Embedding and Its Variants,\" IEEE Society International Conference on Computer Vision and Pattern Computer Society International Conference on Computer Vision Recognition, Salt Lake City, Utah, June 2018. (CVPR) and Pattern Recognition, vol. 1, pp. 679-686, San Diego, CA, USA, June 2005. (CVPR) 180

Research Fellow 蔡懷寬 研 究 Huai-Kuang Tsai 人 員 Ph.D., Computer Science and Information Engineering, Faculty National Taiwan University, Taiwan T +86-2-2788-3799 ext. 1718 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/hktsai ・ Research Fellow, Institute of Information Science, Academia Sinica (2015/11-present) ・ Professor (Joint appointment), Genome and Systems Biology degree program, National Taiwan University (2016/8-present) ・ Professor (Joint appointment), Department of Computer Science and Engineering, National Ocean University (2016/8-present) ・ Professor (Joint appointment), Department of Biological Science and Technology, National Chiao-Tung University (2016/8-present) ・ Associate Professor (Adjunct), Institute of BioMedical Informatics, National Yang-Ming University (2013/8-present) ・ Core faculty, Bioinformatics Program, Taiwan International Graduate Program (TIGP), Academia Sinica (2006/7-present) ・ Editor, Scienti c Reports (2016/9-present) Research Description Bioinformatics is an interdisciplinary eld that combines computer science and biology to analyze biological data. My research interests are functional genomics and pest bioinformatics. For functional genomics, I am interested in understanding the dynamic interactions between cis- and trans-regulatory elements and the evolutionary signatures of genomes. Our recent progresses include (1) transcriptional regulatory mechanism and evolution, (2) epigenetics and enhancer function, and (3) discovery of non-coding RNA (ncRNA) and mRNA isoforms. We recently develop a statistical method to identify the novel factors involving in the transcriptional bu ering during S phase in the budding yeast, which are validated by the biological experiments. By integrating multi-omics data, we are able to show that the divergent transcription factor (TF)-binding motifs tend to be introduced in the edges of cis-regulatory regions across evolutionary time. In addition, we have employed machine learning techniques to investigate the TF binding site prediction and the combinatorial e ect of TFs on alternative splicing of gene transcripts. As emergence of long ncRNAs (lncRNAs) through evolution may hold the potential role in transcriptional regulation, we have demonstrated that a notable portion of lncRNAs were derived from pseudogenized protein-coding genes. Besides, we have constructed the database related to splicing isoforms in di erent organisms and a novel splicing annotation tool. For pest bioinformatics, we apply bioinformatics approaches to help the pest control management. Our applications cover the discovery of gene isoforms in mosquitoes, image classi cation of urban pest insects (e.g. termites and red imported re ants), and the metagenome diversity in the invasive yellow crazy ant. In addition, our team could not only analyze the large amount of biological data but also conduct the interdisciplinary and collaborative research with di erent biology experts, who experimentally validating novel hypotheses generated by our analyses. Publications 1. Chiang, S., Shinohara, H., Huang, J.H., Tsai, H.K.*, and Okada, 6. Tsai, Z.T.Y., Shiu, S.H.*, and Tsai, H.K.* (2015) Contribution of Brochure 2020 M.* (2020) Inferring the transcriptional regulatory mechanism sequence motif, chromatin state, and DNA structure features to of signal-dependent gene expression via an integrative predictive models of transcription factor binding in yeast, PLoS computational approach, FEBS Letters, DOI: 10.1002/1873- Computational Biology, 11(8), e1004418. 3468.13757. 7. Tsai, Z.T.Y., Chu, W.Y., Cheng, J.H., and Tsai, H.K.* (2014) 2. Huang, J.H., Kwan, SY. Tsai, T.Y., and Tsai, H.K.* (2018) Associations between intronic non-B DNA structures and exon Expansion of transcription factor binding sites for introducing skipping, Nucleic Acids Research, 42(2), 739-747. lineage-specific motifs in the promoter regions, Frontiers in Genetics, 9, 571. 8. Chen, Y.C., Cheng, J.H., Tsai, Z.T.Y., Tsai, H.K.*, and Chuang T.J.* (2013) The impact of trans-regulation on the evolutionary 3. Shiau, C.K., Huang, J.H. and Tsai, H.K.* (2018) CATANA: rates of metazoan proteins, Nucleic Acids Research, 41(13), Comprehensive alternative transcript atlas based on annotation, 6371-80. Bioinformatics, bty795. 9. Chen, M.J., Chou, L.C., Hsieh, T.T., Lee, D.D., Liu, K.W., Yu, 4. Liu, W.H., Tsai, Z.T.Y., and Tsai, H.K.* (2017) Comparative C.Y., Oyang, Y.J., Tsai, H.K.* and Chen, C.Y.* (2012) De novo genomic analyses highlight the contribution of pseudogenized motif discovery facilitates identification of interactions between protein-coding genes to human lincRNAs, BMC Genomics, 18, transcription factors in Saccharomyces cerevisiae, Bioinformatics, 786. 28, 701-708. 5. Cheng, J.H., Pan D., Tsai, Z.T.Y., and Tsai, H.K.* (2015) 10. Wang, T.Y., Su, C.H. and Tsai, H.K.* (2011) MetaRank: a Genome-wide analysis of enhancer RNA in gene regulation rank conversion scheme for comparative analysis of microbial across 12 mouse tissues, Scientific Reports, 5, 12648. community compositions, Bioinformatics, 27, 3341-3347. 181

究研 人 Associate Research Fellow 員 穆信成 Shin-Cheng Mu Faculty DPhil (Ph.D.), Computing Laboratory, University of Oxford, United Kingdom T +886-2-2788-3799 ext.730 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/scm ・ Steering Committee Member, International Conference on Functional Programming (2019/09 - 2023/09) ・ Member, IFIP Working Group 2.1 on Algorithmic Languages and Calculi (2010/01-present) ・ Organizer, Lecturer, Formosan Summer School on Logic, Language, and Computation, Taipei, Taiwan (2007-present) ・ Guest Editor, Science of Computer Programming. Speicial Issue for PEPM 2013 (2013/01- 2014/06) ・ Steering Committee Chair, Workshop of Generic Programming Steering Committee (2013/10-2014/10) ・ Co-Chair, ACM SIGPLAN 2013 Workshop on Partial Evaluation and Program Manipulation (PEPM '13), (2013/01-2013/01) ・ PC Co-Chair, Seventh Workshop on Generic Programming (WGP '11), (2011/09-2011/09) ・ Postdoc, University of Tokyo, Information Processing Lab, Japan (2003/6-2006/1) Research Description The main theme of my research is about formal approaches to program construction, in particular, functional and relational approaches to program calculation. The general aim of the eld is to stepwise construct from a problem speci cation, in an algebraic manner, an algorithm that solves the problem. One example involves an elegant algorithm pattern which we nickname \"queueing and glueing'' algorithm. In recent years I am also experimenting with derivation of monadic programs. I believe it will be a good alternative to relational program calculation. In recent years I have also been studying dependently typed programming and theorem proving. While program calculation is traditionally carried out by hand, we developed a library AoPA (Algebra of Programming in Agda) that allows one to encode algebraic, relational proofs into Agda, a dependently typed programming language. We thus gain the best of both worlds ─ clear algebraic proofs that can be read by people may also checked by machine. We hope this helps to improve correctness of program derivation and allows derivation to scale up to much larger programs. On a more theoretical side, we developed theories that allow us to use Galois connection (GC) as a speci cation, from which we may calculate an implementation of the function. The technique is applied to optimisation problems, many of which can be speci ed as a GC, and by doing so we considerably simplified previous theories on calculation of optimisation problems. On the practical side, we developed \"modular rei able matching\" Datatypes à la Carte that has advantages that help with extensibility, modularity and reuse. Publications from relational specifications: a tutorial,\" Journal of Logic and Algebraic Programming, volume 85, number 5, Part 2, pages 879- 1. S-C. Mu and T-J. Chiang, \"Declarative pearl: deriving monadic 905, August 2016. quicksort.\" In Functional and Logic Programming (FLOPS), Keisuke Nakano and Konstantinos Sagonas, editors. April 2020. 7. S. Curtis, S-C. Mu, \"Calculating a linear-time solution to the densest-segment problem,\" Journal of Functional Programming, 2. K. Pauwels, T. Schrijvers and S-C. Mu, \"Handling local state with volume 25, number 0, pages e22 (32 pages), December 2015. global state.\" In Mathematics of Program Construction (MPC), Graham Hutton, editor, pp. 18-44. Springer, October 2019. 8. B. C. d. S. Oliveira, S-C. Mu, S-H. You, \"Modular reifiable matching: a list-of-functors approach to two-level types,\" Haskell 3. C-M. Cheng, R-L. Hsu, and S-C. Mu, \"Functional pearl: Symposium 2015, B. Lippmeier, editor, pages 82-93, September folding polynomials of polynomials.\" In Functional and Logic 2015. Programming (FLOPS), John Gallagher and Martin Sulzmann, editors, pp 68-83, 2018. 9. S-C. Mu, Y-H. Lyu, and A. Morihata, \"Approximate by thinning: deriving fully polynomial-time approximation schemes,\" Science 4. Y-F. Chen, C-D. Hong, O. Lengál, S-C. Mu, N. Sinha, and of Computer Programming, volume 98, number 4, pages 484- B-Y. Wang, \"An executable sequential specification for Spark 515, February 2015. aggregation\". Networked Systems (NETYS), pp. 421-438. 2017. 10. S-C. Mu, T-W. Chen, \"Functional pearl: Nearest shelters in 5. S-C. Mu, Y-H. Chiang, and Y-H. Lyu, \"Queueing and glueing for Manhattan,\" Programming Languages and Systems, Lecture optimal partitioning,\" International Conference on Functional Notes in Computer Science, 8858, pages 159-175, November Programming (ICFP 2016), Eijiro Sumii, editor, ACM Press , 2014. pages 158-167, September 2016. 6. Y-H. Chiang, S-C. Mu, \"Formal derivation of greedy algorithms 182

Research Fellow 蘇克毅 研 究 Keh-Yih Su 人 員 Ph.D., Electrical Engineering, University of Washington, United States Faculty T +86-2-2788-3799 ext. 1801 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/kysu ・ Research Fellow, Institute of Information Science, Academia Sinica (2014/6-present) ・ President/CEO, Behavior Design Corporation (1998-2014) ・ Associate Professor, Professor, Dept. of Electrical Engineering, National Tsing Hua University (1984-1998) ・ Chair, Asia-Paci c Chapter of the Association for Computational Linguistics (2021-2022) ・ Chair-elect, Asia-Paci c Chapter of the Association for Computational Linguistics (2018- 2020) ・ President, Asian Federation of Natural Language Processing (2011-2012) ・ Executive Member, Association for Computational Linguistics (2005-2007) ・ Ph.D., Electrical Engineering, University of Washington (1984) Research Description My research interests include Natural Language Understanding (NLU), Machine Reading, Question and Answering (Q&A), and Chinese Language Processing. I have worked on statistical modeling and machine learning for natural language processing since 1986 (mainly adopting principled approaches to solving NLP problems with domain knowledge, in contrast to the simple data-driven techniques). My past experience mainly lies in: (1) Building a statistical semantic machine translation system, which conducts translation in semantic level and automatically obtains associated parameters via semi-supervised learning. (2) Proposing a joint model to integrate Translation Memory into a phrase-based machine translation system during decoding, which has achieved signi cant improvement. (3) Building both statistics- based and DNN-based Math Word Problem Solvers, which tried to gure out the associated physical meaning of those quantities described in the problem text for providing interpretable reasoning steps. They act as our test cases for studying the problems of Machine Reading and Question Answering. My current main projects are: (1) Building a platform to explore new knowledge from multiple documents, which is supported by the Thematic Program of Academia Sinica, and (2) Designing/Constructing a Conversational Open Domain Document-based Natural Speech Q&A (COSQA) system, which is supported by IIS. The project of exploring new knowledge from multiple documents aims to refine the noisy information extracted from traditional information extraction (IE), and to explore new knowledge across domains. On the other hand, the project of constructing COSQA system not only acts as an ideal testbed for conducting NLU, but also has many real applications such as customer service, medical consultant system, information-seeker, etc. This project will handle following di cult issues at the same time: free-text, multi-document rational, common-sense reasoning, multi-hop inference, pragmatic-reasoning, and natural-speech. Conducting this project will force us to face the real challenge in AI. Publications 1. Qianlong Du, Chengqing Zong, and Keh-Yih Su, \"Conducting 6. Chao-Chun Liang, Yu-Shiang Wong, Yi-Chung Lin and Keh-Yih Brochure 2020 Natural Language Inference with Word-Pair-Dependency and Su, \"A Meaning-based Statistical English Math Word Problem Local Context,\" ACM Transactions on Asian and Low-Resource Solver,\" Proceedings of NAACL-HLT 2018, New Orleans, LA, Language Information Processing, volume 19, number 3, pages U.S.A, June 2018. 47:1-47:23, February 2020.\" 7. Hsin-Wei Yu, Chia-Hung Huang, and Keh-Yih Su, \"Answering 2. Chao-Chun Liang and Keh-Yih Su, \"ASNLU at the NTCIR-14 Yes/No Questions with a Decomposable Attention Model,\" FinNum Task: Incorporating Knowledge into DNN for Financial Proceedings of TAAI 2017, December 2017. Numeral Classification,\" Proceedings of the 14th NTCIR Conference on Evaluation of Information Access Technologies, 8. Chao-Chun Liang ,Yu-Shiang Wong ,Yi-Chung Lin and Keh- Tokyo, Japan, June 2019. Yih Su, \"A Goal-Oriented Meaning-based Statistical Multi-Step Math Word Problem Solver with Understanding, Reasoning and 3. Yang Liu, Kun Wang, Chengqing Zong, and Keh-Yih Su, \"A Explanation,\" Proceedings of IJCAI 2017, Melbourne, Australia, Unified Framework and Models for Integrating Translation August 2017, System Demonstration. Memory into Phrase-based Statistical Machine Translation,\" Journal of Computer Speech and Language, volume 54, pages 9. Qianlong Du, Chengqing Zong and Keh-Yih Su, \"Integrating 176-206, March 2019. Structural Context with Local Context for Disambiguating Word Senses,\" Proceedings of NLPCC-ICCPOL 2016, Kunming, 4. Meng-Tse Wu, Yi-Chung Lin, and Keh-Yih Su, \"Supporting China, December 2016. Evidence Retrieval for Answering Yes/No Questions,\" International Journal of Computational Linguistics and Chinese 10. Chao-Chun Liang, Shih-Hong Tsai, Ting-Yun Chang, Yi-Chung Language Processing, volume 23, number 2, pages 47-66, Lin and Keh-Yih Su, \"A Meaning-based English Math Word December 2018, Its brief version also won the best paper award Problem Solver with Understanding, Reasoning and Explanation,\" in Rocling-2018. Proceedings of COLING 2016, Osaka, Japan, December 2016, System Demonstration. 5. Qianlong Du, Chengqing Zong, and Keh-Yih Su, \"Adopting the Word-Pair-Dependency-Triplets with Individual Comparison for 183 Natural Language Inference,\" COLING 2018, Santa Fe, New Mexico, USA, August 2018.

究研 人 Assistant Research Fellow 員 蘇黎 Li Su Faculty Ph.D., Graduate Institute of Communication Engineering, National Taiwan University, Taiwan T +886-2-2788-3799 ext.1806 E [email protected] F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/lisu/ ・ Best Paper Award of the International Society of Music Information Retrieval Conference (ISMIR), Delft, the Netherlands (2019) ・ Assistant Research Fellow, Institute of Information Science, Academia Sinica, Taiwan (2017-present) ・ Postdoctoral Research Fellow, Center for Information Technology Innovation, Academia Sinica, Taiwan (2012-2016) ・ Ph.D., Graduate Institute of Communication Engineering, National Taiwan University, Taiwan (2008-2012) ・ B.S. (Double Degree), Electrical Engineering & Mathematics, National Taiwan University, Taiwan (2003-2008) Research Description My research interests focus on machine musicianship, the dream of making a machine understand music as a musician does. Research areas for this interdisciplinary topic include automatic music transcription, machine music appreciation, automatic music generation, and computational creativity of music. Applications are found in music production, education, entertainment, well-being, computational musicology, revitalization of music cultural heritage, and others related to next-generation music industry. Research directions are two-fold: the rst is the analysis of scores written by a composer (i.e., automatic music transcription), while the second is the analysis of interpretation in musical performance (i.e., music expression analysis). The core technology I have developed over the past three years is a system for automatic music transcription. Automatic transcription of polyphonic music is the holy grail in machine listening. I proposed a novel method, called the combined frequency and periodicity (CFP) method, which detects pitches according to the agreement of a harmonic series in the frequency domain and a subharmonic series in the lag domain. This approach nicely aggregates the complementary advantages of the two feature domains in di erent frequency ranges, and improves the robustness of the pitch detection function to the interference of the overtones of simultaneous pitches. As an ongoing project, my recent e ort of research is focused on developing virtual musicians, and making them understand the music content, behave with music in reasonable body movements, and even play music with real human. The main research topic to achieve this goal is to develop solutions to jointly generate multi-modal contents including image, motion, audio and a ective information directly from music repertoire. Up to date, we have collected a music dataset containing high-quality music semantic annotation and body movement, and proposed a music-to-body-movement generation framework. The developed virtual musician technologies will add great possibilities in the industry of animation and computer-human interaction. Publications 5. Yu-Te Wu, Berlin Chen, Li Su, \"Polyphonic Music Transcription with Semantic Segmentation,\" IEEE International Conference on 1. Jun-Wei Liu, Hung-Yi Lin, Yu-Fen Huang, Hsuan-Kai Kao, Li Su, Acoustics, Speech and Signal Processing (ICASSP), May 2019. \"Body movement generation for expressive violin performance applying neural networks,\" IEEE International Conference on 6. Chen-Yun Lin, Li Su, and Hau-tieng Wu, \"Wave-shape function Acoustics, Speech and Signal Processing (ICASSP), May 2020. analysis - when cepstrum meets time-frequency analysis,\" Journal of Fourier Analysis and Applications (JFAA), volume 24, number 2. Yu-Fen Huang, Tsung-Ping Chen, Nikki Moran, Simon Coleman, 2, pages 451-505, April 2018. and Li Su, \"Identifying expressive semantics in orchestral conducting kinematics,\" International Society of Music 7. Li Su and Yi-Hsuan Yang, \"Combining Spectral and Temporal Information Retrieval Conference (ISMIR), November 2019. Representations for Multipitch Estimation of Polyphonic Music,\" IEEE/ACM Trans. Audio, Signal Language Proc. (TASLP) , 3. Zih-Sing Fu and Li Su, \"Hierarchical classification networks volume 23, number 10, pages 1600-1612, October 2015. for singing voice segmentation and transcription,\" International Society of Music Information Retrieval Conference (ISMIR), 8. Li Su, Chin-Chia M. Yeh, Jen-Yu Liu, Ju-Chiang Wang, and November 2019. Yi-Hsuan Yang, \"A systematic evaluation of the bag-of-frames representation for music information retrieval,\" IEEE Trans. 4. Tsung-Ping Chen and Li Su, \"Harmony transformer: incorporating Multimedia (TMM) , volume 16, number 5, pages 1188-1200, chord segmentation into harmony recognition,\" International August 2014. Society of Music Information Retrieval Conference (ISMIR), November 2019, (Best Paper Award) 184

Research Fellow 鐘楷閔 研 究 Kai-Min Chung 人 員 Ph.D., Computer Science, Harvard University, United States Faculty T +86-2-2788-3799 ext. 1716 E [email protected] F +886-2-2782-4814 W kwmwcwh.uiisn.gsinica.edu.tw/pages/ ・ Research Fellow, Academia Sinica, Institute of Information Science, Taiwan (2020/2-present) ・ Associate Research Fellow, Academia Sinica, Institute of Information Science , Taiwan (2015/3-2020/2) ・ Assistant Research Fellow, Academia Sinica, Institute of Information Science, Taiwan (2013/9-2015/2) ・ Postdoctoral Research Associate, Cornell University, Department of Computer Science, United States (2010/8-2013/8) ・ Ph.D., Computer Science, Harvard University, United States (2005/9-2011/3) ・ B.S., Computer Science and Information Engineering, National Taiwan University, Taiwan (1996/9-2003/6) Research Description My research lies in the eld of (quantum) cryptography with a broad interest in theoretical computer science. I have worked on classical cryptography for decade, and contributed to several lines of research, such as cryptography for parallel RAM, zero-knowledge, program obfuscation, and delegation of computation. In recent years, my research focuses more on the interdisciplinary field of quantum cryptography, which investigates the role of quantum computation in cryptography. In the following, I highlight my research on cryptography in the parallel RAM model and quantum cryptography. Cryptography for parallel RAM (PRAM) Large data sets, such as medical, genetic, and transaction data are now in abundance. Leveraging the power of massive parallelism and random data access simultaneously is important to handle the big data. However, traditional cryptographic designs typically work with the circuit model, which does not capture random data access, and recent research on cryptography for the RAM model does not capture parallelism. We propose to use the parallel RAM (PRAM) model as a clean abstract model to capture both power, and develop techniques to design cryptographic solutions for the PRAM model. In particular, we de ned and construct the rst oblivious PRAM, obtained general feasibility results based on indistinguishability obfuscations, and constructed the rst adaptively secure garbled PRAM. Quantum cryptography Quantum cryptography aims to understand the role of quantum computation in cryptography, which is a double-edged sword. On one hand, Shor’s quantum algorithm can be used to break most public-key cryptosystems in use. One the other hand, quantum also enhances the honest parties to achieve stronger functionalities or security. We are generally interested in investigating the role of quantum in cryptography on both sides in diverse directions; some of which proposed by us. The topics include device-independent cryptography, understanding the role of quantum (side) information, classical delegation of quantum computation, and security in the quantum random oracle model. Publications 1. Nai-Hui Chia, Kai-Min Chung, Ching-Yi Lai, \"On the Need for 6. Kai-Min Chung, Yaoyun Shi and Xiaodi Wu, \"General Brochure 2020 Large Quantum Depth,\" The 52nd Annual ACM Symposium on Randomness Amplification with Non-signaling Security,\" The Theory of Computing 2020 (STOC 2020), June 2020. 20th Annual Conference on Quantum Information Processing (QIP2017), January 2017. 2. T-H. Hubert Chan, Kai-Min Chung, Wei-Kai Lin and Elaine Shi, \"MPC for MPC: Secure Computation on a Massively Parallel 7. Elette Boyle and Kai-Min Chung and Rafael Pass, \"Oblivious Computing Architecture,\" The 11th Innovations in Theoretical Parallel RAM and Applications,\" The 13rd IACR Theory of Computer Science (ITCS 2020), January 2020. Cryptography Conference (TCC2016), January 2016. 3. Thomas Vidick, Han-hsuan Lin, Divesh Aggarwal and Kai- 8. Kai-Min Chung and Huijia Lin and Rafael Pass, \"Constant- Min Chung, \"A Quantum-Proof Non-Malleable Extractor With Round Concurrent Zero-knowledge from Indistinguishability Application to Privacy Amplification against Active Quantum Obfuscation,\" The 35th International Cryptology Conference Adversaries,\" The 38th Annual International Conference on the (CRYPTO), August 2015. Theory and Applications of Cryptographic Techniques (Eurocrypt 2019), May 2019. 9. Kai-Min Chung and Yaoyun Shi and Xiaodi Wu, \"Physical Randomness Extractors,\" The 17th Conference on Quantum 4. T-H. Hubert Chan, Kai-Min Chung, Bruce Maggs and Elaine Information Processing (QIP) , Renato Renner, editor, February Shi, \"Foundations of Differentially Oblivious Algorithms,\" 2014, Accepted as a *plenary talk* at the 17th Conference on ACM-SIAM Symposium on Discrete Algorithms (SODA 2019), Quantum Information Processing (QIP) February 2014. January 2019. 10. Kai-Min Chung and Rafael Pass and Karn Seth, \"Non-Black- 5. Chi-Ning Chou, Kai-Min Chung and Chi-Jen Lu, \"On the Box Simulation from One-Way Functions And Applications to Algorithmic Power of Spiking Neural Networks,\" The 10th Resettable Security,\" The 45th ACM Symposium on Theory of Innovations in Theoretical Computer Science (ITCS 2019), Computing (STOC), Dan Boneh and Tim Roughgarden and Joan January 2019. Feigenbaum, editor, ACM, pages 231-240, June 2013. 185

究研 人 Assistant Research Engineer 員 林宗慶 Tsung-Ching Lin Faculty M.S., The Institute of Information Management, Tamkang University, Taiwan T +886-2-2788-3799 ext. 1308 E [email protected] F +886-2-2651-8660 W www.iis.sinica.edu.tw/pages/tclin ・ Assistant Research Engineer, Institute of Information Science, Academia Sinica (2007/7-present) ・ Research Assistant, Institute of Information Science, Academia Sinica (2001/10-2007/7) ・ M.S., The Institute of Information Management, Tamkang University (1998) ・ B.S., Information Management, Tamkang University (1994) Research Description I am the Director of Information Center at IIS since July 2019. My work is to support research continuity at IIS by building a suite of information systems that help researchers to easily manage their projects. These systems can assist with oversight of assistant salaries, equipment purchase, expenses and remaining budgets, and more. Researchers may also use the information systems to more easily apply for research budgets. I also built a series of administration information systems to support daily routines of administrators in IIS, including Personnel and Salary Management, Accounting Operation System, Cashier Operation System, Petty Cash Management and IIS Asset Management. A major function of mine is building and maintaining the secured network at IIS. In this work, I established a rewall to protect the network from potential threats and malicious attacks. Employees can easily and securely access resources through a Virtual Private Network from outside IIS, and a mail ltering system has been implemented to block possible malicious and spam mail. My recent work is building a new Personnel and Salary Management System. The new system is more exible and will resolve issues that have arisen from changing of laws, and other new requirements from the past decade. Detailed description of the categories that the new systems will address are listed below: 1. Personnel and Salary Management System 2. Project and Budget Management System 3. Finance Accounting System 4. Cashier and Cheque Management System 5. Petty Cash Management System 6. Summary of Project Executing 7. Business Process Management 8. Attendance Management 186

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支援部門 Supporting Departments

資訊室 190 Computer Services Center 191 192 圖書室 193 Library 194 195 行政室 Administrative O ce 189

資訊室 資訊室位於資訊所新館 308 室及 301 室，目前有九位工作伙伴。其中五位伙伴 負責資訊系統的開發與維護工作，二位伙伴負責資訊所資訊基礎建設及資訊安 全防護工作，二位伙伴負責研究及行政技術人員的電腦技術支援。資訊室主要 任務如下： 1. 資訊安全與個人資料保護 2. 虛擬機器私有雲服務。 3. 研究與行政業務資訊系統的分析、設計、與撰寫。 4. 全所共用伺服主機的安裝與維護。 5. 全所電腦及電話網路的建置與維護。 6. 主要會議室設備正常運作之設計與維護。 7. 行政、技術與研究人員電腦之採購與維護。 8. 各類電腦零組件、耗材及多媒體設備之借用及領用。 9. 資訊所與資創中心共用機房的建置與維護。 10. 資訊不斷電系統的建置與維護。 11. 全所考勤、門禁、監控系統的設計與維護。 資訊所於新館二樓設置電腦機房，供放置公共服務及實驗 線上使用的系統有： 室的資訊設備。機房備有獨立不斷電設備、發電機、恆溫 恆濕空調設備，以提供資訊設備良好的運作環境。電腦機 （1）各類問題回報請修系統如：電腦電話報修、環境 房為高耗能的設施，資訊室為減少能源浪費，逐步調節機 問題回報修繕、行政作業系統問題回報與解決等。 房之用電效率，現在都維持「用電效用」（PUE）在 1.5 至 1.6 之間。依 Green Grid 於 2007 年發佈能源使用效率 （2）各類服務申請如：電子憑證、電腦帳號申請、英 評量指標，屬銀級標準。 文諮詢服務預約、網路及長途電話申請、物品耗 材借領用等。 資訊所重要的網路設備置於新館 301 室，包含有骨幹網路 交換器、防火牆、電話電子交換器、虛擬私人網路伺服主 （3）考勤、門禁安全管控。 機、檔案伺服主機、考勤門禁卡機伺服主機、攝影監控伺 （4）空間管理系統，如：各老師及實驗室空間使用情 服主機、會議實況錄製系統。 形、各會議室預約及會議室即時動態。 為提供大量運算，促進資源充分利用及共享，資訊室提供 （5）人薪系統，如：人員到離職、人員相關資料查詢、 虛擬機器私有雲服務。本所私有雲分為實驗區及服務區。 實驗區私有雲主要運行高運算需求的虛擬機器。此類虛擬 薪資審核發給、考勤系統、請假及加班之申請與 機器提供多核心、大容量記憶體及儲存空間。服務區則運 審核、續聘、工作日誌、公文暨公告管理系統等。 行對外服務的虛擬機器。此類機器主要提供要求服務穩 （6）請購審核、及採購驗收等系統。 定、資料安全的環境。資訊室為服務區之虛擬機器，提供 （7）出差申請管理系統。 即時資料備份及備援設備，若發生設備損壞或資料毀損等 （8）預算系統及會計、出納、零用金等系統。 狀況，可以降低停機時間。依研究人員需求，以自動化流 （9）物品與財產管理系統。 程提出申請並創建虛擬主機。 （10）機房空間管理如機櫃、電源使用， IP 使用等。 （11）專屬研究人員的系統有：個人制式首頁製作、訪 在 資 訊 安 全 方 面， 資 訊 室 設 置 應 用 層 防 火 牆 (Layer 問學人邀請與審核、考績評量、研究經費申請與 7 Firewall)、 網 頁 應 用 程 式 防 火 牆 (Web Application 評估核定、老師各類經費執行狀況。 Firewall， WAF)，以加強阻擋外界的惡意攻擊。資訊室同 （12）資訊設備費概算申請與審核系統。 時設電子郵件過濾器，針對惡意郵件或釣魚信件送達收件 者之前，即可被阻擋隔離，以減少使用者的隱私資料外洩 ( 二 ) 對外服務的系統 的風險。資訊室定時針對所內重要伺服器進行弱點偵測掃 描，使資訊設備的系統漏洞能即時修補，以保持系統正 （1）會議系統： 常運作及確保資料的安全性。設置虛擬私人網路加密通 對於國內外學術會議，提供從線上投稿、審稿， 道 (VPN) 服務，不論同仁在所內外，甚至是海外，皆可安 一直到線上報名與會、信用卡線上繳費等等各式 全存取所內資源。配合中研院資安等級的提昇，資訊室亦 資料管理，及現場報到的服務與管理。 協同院本部資訊服務處，針對一些資安事件進行處置與回 覆。 （2）中研院體育館場地預約系統 （3）智慧型預約與案件申請系統： 為輔助研究人員研究業務順利進行，資訊室將行政與研究 業務逐步資訊化，擔任起行政、助理與研究人員之間溝通 院本部學術儀器處為使用單位，該處統一管理中 的橋樑，所提供的資訊服務系統主要分為以下幾類： 研院各單位所採購的貴重儀器，透過申請系統提 供院內外人員申請預約及使用。 ( 一 ) 行政與研究業務資訊化服務 （4）論文期刊管理系統： 使用單位有中研院資訊所、中研院生物多樣性中 心、中研院語言所等，對於學術期刊的製作，提 供徵文、投稿、審查、校對、檢索等功能。 （5）研發替代役報名申請系統、暑期實習生報名申請 系統 190

Computer Services Center Computer Center is located in rooms 308 and 301 of the 1. Administrative services new IIS building. The are nine members in total, ve sta s Our online system services include: (1) reporting systems are in charge of the development and maintenance of the for all kinds of related issues, such as telephone and information system; two sta s support technical problems computer support, office environment-related support, of both administrative staff and researchers. Th important administrative online system support, etc.; (2) applications functions of the center include: (1) personal data protection for certi cates of authority, IIS accounts, English editing and information security; (2) administrative system-related services, access to internet and long-distance phone calls, analysis, design and development; (3) installation and as well as other computer-related utilities; (3) attendance maintenance of the Institute's servers; (4) installation and and security management; (4) space management, i.e., maintenance of all internet and phone line equipment; (5) utilization of laboratory space, and reservation and real- design and maintenance of conference room equipment; time information systems for meeting rooms; (5) human (6) computer purchasing and technical support for all resources systems for staff reports and resignations, faculty and staff; (7) supply of various computer parts information on personnel, salary reviews and pay, and equipment to faculty and staff; (8) maintenance of attendance, leave, overtime applications and reviews, the Machine Room for IIS and CITI; (9) maintenance of the reappointments, daily to-do lists, announcements, etc.; uninterruptible power supply; (10) design and maintenance (6) purchasing systems that track of the attendance, entrance, and monitoring systems; and the acquisition process from (11) operation of the private cloud service. start to finish; (7) business trip The network devices of IIS are located in room 301 of the systems; (8) accountancy systems new IIS building. They are equipped with a rewall, virtual for budget management; (9) private network server, file server, domain name server, equipment management; (10) DHCP server, mail server, web server, servers for both machine room and server cabinet administrative and research systems, CA server, server management to control the for the door access control system, and a server for the distribution of power and IP; (11) monitoring and real-time conference-recording system. systems specifically designed for Every oor is equipped with a network printer. Scanners and research fellows allowing them other facilities are available for all staff members outside to manage personal web-pages, room 301. invite visiting scholars, evaluate A newly built machine room is located on the second oor of their assistants, as well as manage projects, funds and the new IIS building to facilitate the information equipment budgets; and (12) IT equipment budget applications and of the public and laboratory service. For environmental review systems. purposes, professional engineers designed the machine room to follow Tier 2 (TIA-944) regulation accordingly. The 2. Services to the public new machine room is well organized, resulting in a more a. Conference system with functions including on-line stable, reliable and safe environment. More importantly, submission, paper review, on-line registration, credit- when the PUE dropped from 2.22 to 1.56, we successfully card payments and information management, as well reduced 1415 tons of CO2 emissions per year. It's equivalent as on-site services. to creating 3.8 Da'An Forest Parks (approximately 64 acres). b. Gym reservation system. In terms of electricity expenditure, we saved NTD 7 million c. Smart reservation and case application system used by per year. This reduces our electricity cost and provides a the Department of Academic Affairs and Instrument green environment for doing research work. Services that is responsible for purchasing high-value In order to provide a computer-intensive service, as well as equipment. Our sta use this system to book and use IIS resources and information sharing, a private cloud service that equipment. The system also has an assessment is available for our sta . The private cloud is supported by function to analyze usage and pro tability, which can a multi-core processor with a large memory and storage help us to make plans for future equipment. space capacity, providing applications and automated d. Publication management system used by IIS, Biodiversity processes to create virtual hosts to meet the needs of our Research Center, Institute of Linguistics, amongst research faculty. others, to collect and submit papers, and for review, Regarding information security, we have an equipped Layer proofreading, and data searching. 7 Firewall, Web Application Firewall (WAF) to prevent the e. Research & Development alternative services and malicious attacks from outside. In order to block malicious application systems for Summer Internships. emails or shing attempts, we also installed an email lter to prevent damages from occurring and further reduce the risk of personal privacy leakage. We also perform vulnerability scans regularly for our major servers to ensure reliable system operation and data security. Through our Virtual Private Network Service, our sta can obtain and store data safely even with remote work. To enhance the security level of our main o ce, we also cooperate with the Department of Information Technology Services to manage certain security events and inquiries. To better assist our colleagues with their research, we aim to digitalize all administrative and research procedures, bridging the gaps between administrators, assistants and research fellows. Our services are as follows: 191

圖書室 本所圖書館於 1977 年 6 月本所成立籌備處時設置，主要任務在提 供所內研究人員所需之學術研究文獻資源，同時也對院外大眾提供 學術服務。圖書館位於資訊所新館大樓二樓，館藏主題以計算機科 學與工程為主，有超過 300 種期刊及超過 24,000 冊圖書。圖書館 不僅以建置逾四十年的館藏文獻範圍為傲，歷任館員也都以為讀者 提供親切有效率的服務為工作目標。 近幾年學術期刊、會議文獻、電子書等電子資源數量及服務發展快 速，且為因應圖書館館藏空間日益飽和問題，圖書館已逐年減少紙 本館藏訂購量，轉向以提供電子資源利用為主。另一方面也朝提供 個人化服務努力，不論文獻檢索或全文提供，期能隨時滿足研究人 員的資訊需求，發揮學術圖書館支援研究的功能。 192

Library Founded in June 1977, the Library of the Institute of Information Science (IIS) supports all research activities of the Institute and provides general service to the public as well. We are located on the second oor of the new IIS building. Our main archives in Computer Science and Engineering cover more than 300 journal titles and 24,000 book volumes. IIS library is not only proud of the scale of our literature collection that has been built over the past forty years, but also the friendly and e cient services provided by our librarians. Due to both space limitations and electronic resources availability, such as journals, conference proceedings, books, and databases, IIS library has been replacing a number of paper-based archives subscriptions with electronic resource access. We even customize professional services for our sta s with special request, including archive and full-text searching. We always aim to better serve the academical needs of our researchers and take that as our mission at the Institute. 193

行政室 行政室位於本所前館大樓二樓，為處理全所行政庶務及營繕業務之 核心。除了設有所長辦公室，另設置祕書室承辦收發文、各項會 議、學術活動、研究人員之新聘 / 升等 / 續聘及合聘等各類聘案業 務。 此外，人事、會計、出納承辦人處理新進人員之報到 / 離職、加 / 退勞健保、薪資、報帳及出納等業務。本所總務同仁，除了負責採 購、財產管理之相關事宜外，另有一組總務同仁負責全所各項維護 及修繕工程等業務。另於同館三樓設有國際學程辦公室專責協助處 理本所的國際研究生相關工作。期刊室則位於圖書館內， 專責本 所發行之 Journal of Information Science and Engineering 編輯工作。 所內行政同仁的努力受到本院的肯定，多次評比獲得績效考評績優 的單位 ！ 本所之行政與研究業務資訊化由本所資訊室執行已陸續完成，例如 公文管理、公告及通知，已充分與行政技術人員的工作日誌整合， 行政人員皆擁有及維護屬於自己承辦業務的網頁。其他一般服務 的項目，例如研討室的預約、物品借領管理、維修申請、電子投票 系統，以及複雜的經費申請、評估與核准、及學術成果均已上網， 一般採購流程由請購、審核、採購、驗收、到轉入會計帳、物品管 理等都已經全部整合在一起。資訊室開發的「學術研討會議管理系 統」並已運用於多個大型國際研討會之籌辦。行政管理之全面資 訊化是我們努力的目標，以期能為全所同仁提供高品質、高效率、 透明化之行政及支援服務。 194

Administrative Office The Administrative Division provides administrative support to the IIS. The Administration offices are mainly located on the second floor of the old IIS building, speci cally: Room 204: Director's O ce & Secretary's O ce Room 206: Human Resources O ce Room 212: Accounting O ce Room 214 and 215: General A airs O ce Room 303: Taiwan International Graduate Program (TIGP) O ce Room 203 (New Building): Editorial Office of the Journal of Information Science and Engineering As the Institute of Information Science, most of our administrative and operational services are now computerized. For example, official announcement and bulletin management systems are integrated with the employee white pages to ensure important information is delivered to relevant staff. Also, the accounting sub-system enables the accounting o ce to conduct all procedures online (from purchase ordering, expenditure account screening, expense authorizing, invoice write-off, to payment processing), and provides a real-time budget summary for the users. We always try to provide better quality, more e cient and transparent services to all of our colleagues in the Institute. IIS Administrative staff have been recognized by Academia Sinica for our high efficiency and professional services. We have been honored with the Excellent Performance Reward for years in the Administration Review on campus due to our outstanding administrative team! 195

Every job is a self portrait of those who did it Autograph your work with quality 發行人：廖弘源 / 中央研究院資訊科學研究所 編 輯：秘書室 出版日期：2020.06 地 址：115台北市南港區研究院路二段128號 電 話：02-27883799 傳 真：02-27892910 Publisher: Mark Liao / Institute of Information Science, Academia Sinica Editor: Secretary O ce Publication Date: 2020.06 Address: No.128, Sec. 2, Academia Road, Nankang, Taipei 115, Taiwan Tel: +886-2-27883799 Fax: +886-2-27892910 https://www.iis.sinica.edu.tw/ 設計製作：數博互動行銷有限公司 / [email protected]