Dr. Tian Li

Biography

Tian Li is an Assistant Professor at the University of Chicago, specializing in Computer Science and Data Science. His research centers on distributed optimization, federated learning, and trustworthy machine learning. He is particularly interested in designing, analyzing, and evaluating principled learning algorithms that take into account practical constraints and address issues related to accuracy, scalability, and trustworthiness. He obtained his Ph.D. in Computer Science from Carnegie Mellon University, where he gained significant recognition, including the Paper Award at the ICLR Workshop on Secure Machine Learning Systems, and was invited to participate in the EECS Rising Stars Workshop. Tian has been recognized as a Rising Star in Machine Learning and Data Science by multiple institutions, further highlighting his contributions to the field. His research focuses on applications of computer algorithms for making data-centric models, predictions, and decisions, particularly in systems that require managing and analyzing data at scale.

Research Interests

Experience

Awards