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特聘講座/特聘研究員｜ Distinguished Chair and Distinguished Research Fellows

Experience Awards
● Distinguished Research Fellow, Institute of Information Science, NSC Appointed Outstanding Research Award (國科會傑出特約研究
許聞廉 Wen-Lian Hsu Academia Sinica (2008-present) 員獎 )(2005)
● Research Fellow, Institute of Information Science, Academia Sinica Academia Sinica Investigator Award (中央研究院深耕獎 )(2005)
(1989-2008) IEEE Fellow (2006)
● Professor (joint appointment), National Tsing Hua University
Teco Award (東元獎 )(2008)
特聘研究員 Distinguished Research Fellow (2003-present) Editorialships
Ph.D., Operations Research, Cornell University ● Visiting Professor, City University of Hong Kong (2004/01-04) International Journal of Foundations of Computer Science (1993-
Education
Tel: +886-2-2788-3799 ext. 1804 ● Ph.D., Operations Research, Cornell University, (1980) 2001, 2009-)
Fax: +886-2-2782-4814 ● M.S., Operations Research, Cornell University, (1978) Journal of Information Science and Engineering (1994-2000, Manag-
Email: hsu@iis.sinica.edu.tw ● B.S., mathematics, National Taiwan University, (1973) ing Editor 1995-2001, Editor in Chief 2010-)
http://iasl.iis.sinica.edu.tw/hsu/ Information Processing Letters (2001-)

代表著作 Publications

1. W. L. Hsu, “Maximum weight clique algorithms for circle graphs and 18. Chuan-Yih Yu, Yin-Hao Tsui, Yi-Hwa Yian, Ting-Yi Sung, and Wen-
circular-arc graphs,” SIAM J. Computing, 14, 224-231, (1985). Lian Hsu*, “The Multi-Q Web Server for Multiplexed Protein Quan-
研究簡介 Research Description 2. W. L. Hsu, “Decomposition of perfect graphs,” J. Combin. Theory, titation,” Nucleic Acids Research.35, W707-712, (2007).
43, 70-94, (1987). 19. Allan Lo, Hua-Sheng Chiu, Ting-Yi Sung, Ping-Chiang Lyu, and
我的研究可分為三個方面：圖論演算法、自然與言理 My main research interests include: (1) graph algorithms; (2) natural language un- 3. W. L. Hsu, “Recognizing planar perfect graphs,” J. Assoc. Comput. Wen-Lian Hsu*, “Enhanced membrane protein topology prediction
解，與生物資訊。 derstanding; and (3) bioinformatics. Machin., 34, 255-288, (1987). using a hierarchical classification method and a new scoring func-
tion,” Journal of Proteome Research 7, 487-496, (2008).
在圖論演算法上，我們發展出一個資料結構「PC-tree」 In graph algorithms, we have done extensive and groundbreaking work on two fun- 4. W. L. Hsu, “The coloring and maximum independent set problems on 20. Jia-Ming Chang, Emily Chia-Yu Su, Allan Lo, Hua-Sheng Chiu,
planar perfect graphs,” J. Assoc. Comput. machin., 535-563, (1988).
，能夠大量簡化辨認平面圖和區間圖的困難度。PC-tree damental classes of special graphs, namely planar graphs and interval graphs, and Ting-Yi Sung, Wen-Lian Hsu, “PSLDoc: Protein subcellular locali-
可以很自然地表達平面圖，並可以統合連續一與環狀一 their related graphs (such as circular arc graphs and circle graphs). We introduced 5. C. Gabor, W. L. Hsu and K. Supowit, “Recognizing circle graphs in zation prediction based on gapped-dipeptides and probabilistic latent
的辨識。我們利用PC-tree所設計出來的平面圖辨認法， a new data structure [2], called PC-tree, which greatly simplifies the recognition of polynomial time,” J. Assoc. Comput. Machin., 435-473, (1989). semantic analysis,” to appear in PROTEINS: Structure, Function, and
Bioinformatics.
極為簡單、直觀，並可藉以發展出一個『極大平面圖』 these two classes of graphs. PC-tree algorithms can unify the tests of consecutive 6. W. K. Shih, W. L. Hsu and T. C. Chen, “An O(n2logn) algorithm for
的線性演算法。 ones property and the circular ones property [10]. Furthermore, PC-tree is a natural the Hamiltonian cycle problem on circular-arc graphs,” SIAM J. Com- 21. Cheng-Wei Lee, Min-Yuh Day, Cheng-Lung Sung, Yi-Hsun Lee,
put., 21, 1026-1046 , (1992).
Tian-Jian Jiang, Chia-Wei Wu, Cheng-Wei Shih, Yu-Ren Chen, Wen-
representation for planar graph embedding. Our new planarity test based on PC- Lian Hsu*, “Boosting Chinese Question Answering with Two Light-
在自然語言方面，我們小組所發展的注音自動轉國字的 trees is simple, elegant and yields a linear time algorithm for finding maximal planar 7. W. L. Hsu, “O(mn) algorithms for the recognition and isomorphism weight Methods: ABSPs and SCO-QAT,” ACM Transaction on Asian
軟體『自然輸入法』，正確率接近96%，曾獲得1993年 subgraphs. problems on circular-arc graphs,” SIAM J. Comput., 24, 411-439, Language Information Processing 7(4), (2008).
傑出中文資訊產品獎。自然輸入法改變了國人認為注音 (1995).
輸入窒礙難學的觀念，在台灣約有一百萬多萬人使用。 In the field of natural language processing, we have designed a Chinese input sys- 8. W. K. Shih and W. L. Hsu, “A new planarity test,” Theoretical Com- 22. Hong-Jie Dai, Chi-Hsin Huang, Ryan T. K. Lin, Richard Tzong-Han
Tsai, and Wen-Lian Hsu, “BIOSMILE web search: a web application
我們另一項重要的成果是，發展出一套『智慧型知識表 tem called GOING, which automatically translates a phonetic (or Pinyin) sequence puter Science, 223, 179-191, (1999). for annotating biomedical entities and relations,” Nucleic Acids Re-
達系統』(InfoMap)，可以適用於許多應用系統的知識管 into characters with an accuracy rate close to 96%. It received the Distinguished 9. W. L. Hsu and T. H. Ma, “Substitution decomposition on chordal search 36, W390-W398, (2008).
理。利用這個系統模擬人類理解的能力，可以在數學教 Chinese Information Product Award (中文傑出資訊產品獎 )in 1993. It is being used graphs and its application,” SIAM J. Comput., 28, 1004-1020, (1999). 23. Allan Lo, Yi-Yuan Chiu, Einar Andreas Rødland, Ping-Chiang Lyu,
學及中文教學上扮演教學助理的角色，也可以在許多自 by more than a million people in Taiwan nowaday. Another achievement is the de- 10. W. L. Hsu, “A simple test for the consecutive ones property”, J. Algo- Ting-Yi Sung*, and Wen-Lian Hsu*, “Predicting helix-helix interac-
然語言系統中整合各種來源的知識。在2005及2006年日 velopment of a knowledge inference kernel, InfoMap, for the semantic analysis of rithms, 42, 1-16, (2002). tions from residue contacts in membrane proteins,” Bioinformatics
本東京舉行的『中文問答系統』比賽，我們實驗室獲得 natural language, which can be applied to a wide variety of application systems in 11. W. L. Hsu and R. McConnell, “PC-trees and circular-ones arrange- 25(8), 996-1003, (2009).
最佳成績。在2009年國際基因名稱搜尋競賽中，也獲得 natural language processing, biological knowledge bases, automation of pipeline ments” Theoretical Computer Science, 296(1), 99-116, (2003). 24. Chih-Chiang Tsou, Yin-Hao Tsui, Yi-Hwa Yian, Yi-Ju Chen, Chuan-
第一名。 experiments, and e-learning. In 2005 and 2006, we won the 1st place in the Chinese 12. W. F. Lu and W. L. Hsu. “A Test for the Consecutive Ones Property Yih Yu, Han-Yin Yang, Ke-Shiuan Lynn, Yu-Ju Chen, Ting-Yi Sung*,
and Wen-Lian Hsu*, “MaXIC-Q Web: A Fully Automated Web Serv-
Question Answering contest in NTCIR held in Tokyo, Japan. In 2009, we won the 1st on Noisy Data - Application to Physical Mapping and Sequence As-
在生物資訊上，我們發展出一套 DNA 序列合成的容錯演 place in BioCreative II.5 gene normalization task. sembly,” Journal of Computational Biology 10(5), 709-735, (2004). ice Using Statistical and Computational Methods for Protein Quanti-
算法。在蛋白質結構與功能預測問題上，我們結合了生 13. K. P. Wu, H. N. Lin, J. M. Chang, T. Y. Sung, and W. L. Hsu, “HY- tation Based on Stable Isotope Labeling and LC-MS,” Nucleic Acids
Research 37, W661-W669, (2009).
物知識庫與機器學習技巧，將準確度推向新的高峰。在 In bioinformatics, we have produced an error-tolerant algorithm for the physi- PROSP: A Hybrid Protein Secondary Structure Prediction Algorithm
質譜儀的蛋白質計量上我們發展的整合性軟體系統受到 cal mapping and the clone assembly problem. Our software for protein quantita- - a Knowledge-Based Approach,” Nucleic Acids Research 32(17), 25. Chih-Chiang Tsou, Chia-Feng Tasi, Ying-Hao Tsui, Putty-Reddy Su-
dhir, Yi-Ting Wang, Yu-Ju Chen, Jeou-Yuan Chen, Ting-Yi Sung, and
了國際間的重視。此外，我們結合了生物、醫學知識以 tion has received a lot of attention. We have also developed machine learning and 5059-5065, (2004). Wen-Lian Hsu, “IDEAL-Q: An automated tool for label-free quantita-
及機器學習的技巧，在生醫文獻上能夠成功地搜尋到許 knowledge-based algorithms for protein structure and function prediction as well 14. Wing-Kwong Wong, Sheng-Cheng Hsu, Shih-Hung Wu, Cheng-Wei tion analysis using an efficient peptide alignment approach and spec-
多使用者有興趣的文章。 as protein interaction interface prediction. We have successfully produced biologi- Lee, and Wen-Lian Hsu*, “LIM-G: Learner-initiating Instruction tral data validation,” Molecular & Cellular Proteomics 9, 131-144,
cal entity and relation recognition algorithms integrating biological knowledge and Model based on Cognitive Knowledge for Geometry Word Problem (2010).
Comprehension,” Computers and Education 48, 582-601, (2007).
machine learning techniques.
15. Hsin-Nan Lin, Kuen-Pin Wu, Jia-Ming Chang, Ting-Yi Sung and
Wen-Lian Hsu, “GANA – A Genetic Algorithm for NMR Backbone
Resonance Assignment,” Nucleic Acids Research 33(14), 4593-4601,
(2005).
16. Hsin-Nan Lin, Jia-Ming Chang, Kuen-Pin Wu, Ting-Yi Sung and
Wen-Lian Hsu, “A knowledge-based hybrid method for protein sec-
ondary structure prediction based on local prediction confidence,”
Bioinformatics 21, 3227-3233, (2005).
17. Kuen-Pin Wu, Jia-Ming Chang, Jun-Bo Chen, Chi-Fon Chang,
Wen-Jin Wu, Tai-Huang Huang, Ting-Yi Sung and Wen-Lian Hsu*,
“RIBRA-an Error-Tolerant Algorithm for the NMR Backbone As-
signment Problem,” Journal of Computational Biology 13, 229-244,
(2006).

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