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Electrical and Computer Engineering

Xiaodan Zhu

Xiaodan Zhu, Ph.D

Assistant Professor

Dept. of Electrical and Computer Engineering
Queen's University
Walter Light Hall 601
19 Union Street
Kingston, ON K7L 3N6

xiaodan.zhu@queensu.ca

Dr. Ali Etemad

Research Interests

Machine Learning, Natural Language Processing, Deep Learning, Artificial Intelligence.

Google scholar profile

Biography

Dr. Xiaodan Zhu is an Assistant Professor of the Department of Electrical and Computer Engineering, and the director of the Text Analytics and Machine Learning Lab. (TAML) at Queen's University. He is also a member of the computer and software engineering group. He received his Ph.D. from the Department of Computer Science at the University of Toronto in 2010 and M.S. from the Department of Computer Science at Tsinghua University in 2000.

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, NAACL, EACL, IEEE/ACM TASLP, JASIST, JAMIA, IPM, etc. His recent work has received the Adam Kilgarriff *SEM Best Paper Award for Lexical Semantics.

Dr. Zhu has rich experience with industry. In the past, he has worked with top industrial research labs, either as a full-time researcher (Intel's China Research Center), a research intern (Google Inc., IBM T.J. Watson Research Center), or as a visiting scholar (Microsoft Research Asia). 

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 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.

For more details, please visit Xiaodan's webpage:  www.xiaodanzhu.com