I am Tian Li, a fifth-year PhD student in Computer Science Department at Carnegie Mellon University working with Virginia Smith. Prior to CMU, I received undergraduate degrees in Computer Science and Economics from Peking University in 2018.
My research centers around optimization, trustworthy machine learning, and learning in heterogeneous environments, with applications to federated learning. I am interested in designing, analyzing, and evaluating principled learning algorithms, taking into account real-world constraints (e.g., communication and heterogeneity) to address issues related to accuracy, scalability, trustworthiness (fairness, robustness, and privacy), and their interplays.
