Tian Li
About
Tian Li is an Assistant Professor of computer science. Her research centers around distributed optimization, federated learning, and trustworthy ML. She is interested in designing, analyzing, and evaluating principled learning algorithms, taking into account practical constraints, to address issues related to accuracy, scalability, trustworthiness, and their interplays. Tian received her Ph.D. in Computer Science from Carnegie Mellon University. Prior to CMU, she received her undergraduate degrees in Computer Science and Economics from Peking University. She received the Best Paper Award at the ICLR Workshop on Secure Machine Learning Systems, was invited to participate in the EECS Rising Stars Workshop, and was recognized as a Rising Star in Machine Learning/Data Science by multiple institutions.
Research Performance Summary
First Recorded Paper
An overreaction to the broken machine learning abstraction: The ease. ml vision
Year: 2017
Citations: 10
Venue: Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics
Latest Recorded Paper
Asynchronous Heavy-Tailed Optimization
Year: 2026
Citations: 0
Venue: arXiv preprint arXiv:2602.18002
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.