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.
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2023
First Place, U.S. Privacy-Enhancing Technologies Pandemic Challenge
2022
Rising stars in EECS workshop
Rising stars in data science UChicago
Top 5% oral presentation at NeurLPS
2021
Best paper award, ICLR
Outstanding reviewer award, NeurLPS
Top 10% reviewers, ICML
Rising stars in machine learning UMD
2020
CMU A. Nico Habermann Educational Service Award
2017
Student summer research fellowship ETHZ
2016
Selected into CS Elite Class at Peking University