Hui Wan  Hui Wan photo         

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Research Staff Member
Thomas J. Watson Research Center, Yorktown Heights, NY USA
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Degrees

  • Ph.D., Computer Science, State University of New York at Stony Brook, 2010
  • M.E., Computer Science, Chinese Academy of Sciences, 2003
  • B.E., Computer Science, Special Class for Gifted Young, University of Science and Technology of China, 2000

 

 

Publication

  • Tahira Naseem, Abhishek Shah, Hui Wan, Radu Florian, Salim Roukos and Miguel Ballesteros, Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning, Association for Computational Linguistics (ACL) pp. 4586-4592, 2019, Florence, Italy.
  • Hui Wan, Tahira Naseem, Young-Suk Lee, Vittorio Castelli, Miguel Ballesteros, IBM Research at the CoNLL 2018 Shared Task on Multilingual Parsing, Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pp. 92-102, Association for Computational Linguistics, 2018. Brussels, Belgium.
  • Haifeng Qian, Hui Wan, Mark N. Wegman, Luis A. Lastras, Ruchir Puri, Measuring Graph Proximity with Blink Model, International Workshop on Mining and Learning with Graphs (a KDD workshop), 2016.
  • Hui Wan, Michael Kifer, Benjamin N. Grosof, Defeasibility in Answer Set Programs with Defaults and Argumentation Rules, Semantic Web Journal, volume 6, Number 1, pp. 81-98, 2015.
  • Hui Wan, Michael Kifer and Benjamin Grosof, Defeasibility in Answer Set Programs via Argumentation Theories, Proceedings of 4th International Conference on Web Reasoning and Rule Systems (RR), pp.149-163, 2010
  • Hui Wan and Michael Kifer, Belief Logic Programming: Uncertainty Reasoning with Correlation of Evidence, Proceedings of 10th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), pp. 316-328, 2009
  • Hui Wan and Michael Kifer, Query Answering in Belief Logic Programming, Proceedings of 3rd International Conference on Scalable Uncertainty Management (SUM), pp. 268-281, 2009
  • Hui Wan, Belief Logic Programming with Cyclic Dependencies, Proceedings of 3rd International Conference on Web Reasoning and Rule Systems (RR), pp. 150-165, 2009
  • Hui Wan, Belief Logic Programming, Proceedings of 25th International Conference on Logic Programming (ICLP), pp. 547-548, Lecture Notes in Computer Science, Springer-Verlag, 2009.
  • Hui Wan, Benjamin Grosof, Michael Kifer, Paul Fodor and Senlin Liang, Logic Programming with Defaults and Argumentation Theories, Proceedings of 25th International Conference on Logic Programming (ICLP), pp. 432-448, 2009
  • Senlin Liang, Paul Fodor, Hui Wan and Michael Kifer, OpenRuleBench: An Analysis of the Performance of Rule Engines, Proceedings of 18th International World Wide Web Conference (WWW), pp. 601-610, 2009
  • Andrew Byde, Hui Wan and Steve Cayzer, Personalized Tag Recommendations via Social Network and Content-based Similarity Metrics, International Conference on Weblogs and Social Media (ICWSM), 2007
  • Hui Wan and Michael Kifer, Belief Logic Programming and its Extensions, Technical Report, Stony Brook University, 2009
  • Guizhen Yang, Michael Kifer, Hui Wan and Chang Zhao, FLORA-2: User's Manual, http://flora.sourceforge.net/docs/floraManual.pdf, 2008

 

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