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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