Xiaodan Zhu

Assistant Professor



Dr. Xiaodan Zhu is an Assistant Professor of the Department of Electrical and Computer Engineering. He leads the Text Analytics and Machine Learning Lab (TAML). Dr. Zhu received his Ph.D. from the Department of Computer Science at the University of Toronto in 2010 and his Masters of Engineering from the Department of Computer Science and Technology at Tsinghua University in 2000. He was a researcher of National Research Council Canada from 2010 to 2017.

Dr. Zhu and his students published at top machine learning, natural language processing, and artificial intelligence conferences and journals such as ICML, ACL, IJCAI, JAIR, IEEE/ACM TASLP, JASIST, JAMIA, NAACL, EACL, IPM, etc. His recent work has received the Adam Kilgarriff *SEM Best Paper Award for Lexical Semantics.

Dr. Zhu has much experience with industry. Rencently, he help Creative Destruction Lab at Rotman School of Managemen of University of Toronto review startup companies' proposals. As another example, he is consulting for IflyTek Inc, a speech and natural language processing company ranked the 6th in MIT Technology Review's "50 smartest company 2017". In the past, he has worked with top industrial research labs either as a research intern (Google (New York), IBM T.J. Watson Research Center), a visiting scholar (Microsoft Research Asia), or as a full-time researcher (Intel's China Research Center).

He is an Associate Editor of the Computational Intelligence journal. He also served other academic committees, e.g., recently as the Publication Chair of COLING-2018, an Area Chair for ACL-2018 and for COLING-2018, and a Steering Committee Member of SemEval-2018. He is an active reviewer for NIPS, AAAI, AISTATS, IJCAI, ACL, TKDE, EMNLP, ICASSP, TASLP, COLING, JBI, ICASSP, INTERSPEECH, ect.

Dr. Zhu is an Evaluation Group Member of NSERC Discovery Grants (Computer Science Group, 2016-2019), Canada. He also served as an external reviewer for government grants such as General Research Fund (GRF), Hong Kong; Faculty Development Scheme (FDS), Hong Kong; Discovery Grants, Canada; Industrial Research & Development Fellowship, Canada.