معرفی
Liu Han is the Orrington Lunt Professor of Computer Science at Northwestern University, with a courtesy appointment in Industrial Engineering & Management Sciences. He directs the MAGICS (Modern Artificial General Intelligible and Computer Systems) Lab and the Center for Foundation Models and Generative AI (CFMG). Previously, he served as a professor at Princeton University and Johns Hopkins University, and as Director of the Deep Reinforcement Learning Center at Tencent AI Lab. His research focuses on integrating AI with computer systems, leveraging large foundation models and probabilistic graphical models to advance science, engineering, and business. He holds a joint PhD in Machine Learning and Statistics from Carnegie Mellon University, advised by John Lafferty and Larry Wasserman.
Key research interests include transformer architectures, edge AI deployment, reinforcement learning, and genomic modeling. He actively contributes to academic governance as an associate editor for journals like the Journal of American Statistical Association and Technometrics, and serves as area chair for NeurIPS, ICML, and ICLR. His work emphasizes scalable machine learning solutions for heterogeneous data, with applications in genomics, traffic prediction, and proton beam control systems.
- Awards: Presidential Early Career Award (2025?), Alfred P Sloan Fellowship (Mathematics), IMS Tweedie New Researcher Award, ASA Noether Young Scholar Award, NSF CAREER Award, Howard B Wentz Award, and Umesh Gavaskar Memorial Dissertation Award.
- Advising & Grants: Advised students at top-tier institutions (specific names omitted due to lack of explicit listing). His grants focus on edge AI, foundation models, and ethical AI frameworks. Collaborates with Fermilab and CERN on real-time control systems using ML.
- Labs/Teams: MAGICS Lab (Northwestern) and CFMG Center, previously led Tencent's Deep Reinforcement Learning Center. Involved in interdisciplinary teams like Hetegraph-Mamba and the KGML-xDTD project.
