Research Scientist at Shenzhen Research Institute of Big Data
Research Associate Professor at The Chinese University of Hong Kong, Shenzhen
Artificial Intelligence, Machine Learning
BSc. in Computer Science, Shandong University
MEng. in Computer Science, Chinese Academy of Sciences
Ph.D in Computer Science and Engineering, The Chinese University of Hong Kong
1) Presidential Exemplar Teaching Award, CUHK-SZ, 2021.
2) Best Paper Finalist (short paper), ACM-CIKM’2021.
3) Best Paper Finalist, IEEE-ICAL’2011.
4) Best Paper in Logistics Award, IEEE-ICAL’2010.
Dr. Li conducted postdoctoral research at The Chinese University of Hong Kong and the University of Alberta, Canada from 2007 to 2009, and taught at the Macau Polytechnic Institute from 2009 to 2016. In August 2016, Dr. Li joined The Chinese University of Hong Kong (Shenzhen) and Shenzhen Institute of Big Data, engaged in teaching and research work in the field of computer and information science.
Dr. Li has published more than 40 first-author papers in the field of machine learning and artificial intelligence, and has completed 6 basic research projects funded by the government. He has served as the organizer and reviewer of many academic conferences such as NIPS, IJCAI, and AAAI.
1) Li Wenye, Yu F., Ma Z. (2023) Metric Nearness Made Practical. In The 37th AAAI Conference on Artificial Intelligence (AAAI’2023).
2) Li Wenye, Yu F. (2022) Calibrating Distance Metrics Under Uncertainty. In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2022
3) Li Wenye (2020) Modeling Winner-Take-All Competition in Sparse Binary Projections. In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2020 (ECML’2020).
4) Li Wenye, Mao J., Zhang Y., Cui S. (2018) Fast Similarity Search viaOptimal Sparse Lifting. In Advances in Neural Information Processing Systems 31 (NeurIPS’2018).
5) Li Wenye, Zhang J., Zhou J., Cui L. (2018) Learning Word Vectors with Linear Constraints: A Matrix Factorization Approach. In 27th International Joint Conference on Artificial Intelligence (IJCAI’2018).