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Xu Zenglin

Professor
Computer Science and Technology
University of Electronic Science and Technology of China
China

Biography

Professor Xu is a member of China 1000-Talents (Youth) Program, and a full professor and PhD Advisor, University of Electronic Science & Technology of China (UESTC). He obtained his PhD in Computer Science and Engineering from the Chinese University of Hong Kong. His research interest includes machine learning and its applications on social network analysis, health informatics, and cyber security analytics. Furthermore, he had published more than 50 papers in the top conferences and journals of machine learning, including NIPS, ICML, IJCAI, AAAI, IEEE TPAMI and IEEE TNN. Together with Professor Alan Qi, he taught a tutorial in AAAI 2012, Toronto, Canada. He is the recipient of the best student paper honorable mention of AAAI 2015, and the best student paper award runner up of ACML 2016. He is also the recipient of Young Researcher Award of APNNS. Dr. Xu has been a PC member or reviewer to a number of top conferences such as NIPS, ICML, AAAI, IJCAI, etc. He regularly servers as a reviewer to IEEE TPAMI, JMLR, Pattern Recognition, IEEE TNNLS, IEEE TKDD, ACM TKDD, etc. He is also a reviewer to National Science Foundation China, Hong Kong Research Grant Council, and the Ministry of Science and Technology of China. Education experience: Education: 1998.09-2002.06 B.S. Xi'an Polytechnic University Computer Science and Technology 2002.09-2005.06 M.S Xi'an Jiaotong University Computer Software and Theory 2005.09-2009.06 Ph.D. The Chinese University of Hong Kong Computer Science and Engineering

Research Interest

Theory of Computation;  artificial intelligence and Pattern recognition; Computer graphics and image processing; Cloud computing and big data processing; Digital Media Technology.

Publications

  • Zenglin Xu, Mingzhen Mo, and Irwin King. Computational intelligence. In Alexandru Floares, editor, Semi-supervised Learning, pages 1-16. Nova Science Publishers, 2012.

  • Zenglin Xu, Irwin King, and Michael R. Lyu. More Than Semi-supervised Learning: A Unified View on Learning with Labeled and Unlabeled Data. LAP LAMBERT Academic Publishing, 2010.

  • Yi Fang, Zenglin Xu, Jiang Bian, and Ziad Al Bawab. International Journal of Web Science, Special Issue on Social Web Search and Mining. Inderscience, 2013.

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