We are in the exciting era where AI and Database technologies are colliding and merging. In this talk, I will introduce the motivations and several opportunities to integrate machine learning/deep learning and database research, in both directions. As a case study, I will focus on a new deep learning-based model for range selectivity estimation for high-dimensional data. The model is guaranteed to be consistent, i.e., monotonic in the threshold parameter, and has demonstrated superior performance against state-of-the-art methods in all error measures across several datasets and distance/similarity functions.

Dr. Wei Wang is a Professor in the School of Computer Science and Engineering, The University of New South Wales, Australia. His current research interests include Similarity Query Processing, Artificial Intelligence, Knowledge Graphs, and Security for AI Models. He has published over a hundred research papers, with many in premier database journals (TODS, VLDB J, and TKDE) and conferences (SIGMOD, VLDB, ICDE, WWW, IJCAI, AAAI, ACL). More can be found on his homepage at: http://www.cse.unsw.edu.au/~weiw/