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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 tshsu@iis.sinica.edu.tw
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
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 tshsu@iis.sinica.edu.tw
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
