Han Liu
About
Han Liu directs the MAGICS (Modern Artificial General Intelligible and Computer Systems) lab at the Northwestern University. He has been the director of the deep reinforcement learning center at Tencent AI Lab and had been a professor at the Princeton University and Johns Hopkins University. He received a joint PhD in Machine Learning and Statistics from the Machine Learning Department at the Carnegie Mellon University, advised by John Lafferty and Larry Wasserman. His research lies at the intersection of artificial intelligence and computer systems, which deploys statistical machine learning methods on edges and clouds to achieve analytical advantages. Han Liu has received numerous research awards including the Alfred P Sloan Fellowship in Mathematics, the IMS Tweedie New Researcher Award, the ASA Noether Young Scholar Award, the NSF CAREER Award, the Howard B Wentz Award and the Umesh Gavaskar Memorial Best Dissertation Award. He is now serving as associate editors for the Journal of American Statistical Association, the Electronic Journal of Statistics, the Technometrics, and the Journal of Portfolio Management.
Research Performance Summary
First Recorded Paper
On efficient and effective association rule mining from XML data
Year: 2004
Citations: 16
Venue: International Conference on Database and Expert Systems Applications
Latest Recorded Paper
Universal Approximation with Softmax Attention
Year: 2025
Citations: 0
Venue: arXiv e-prints, arXiv: 2504.15956
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.