Email: litian@uchicago.edu
(Note: My CMU email address does not work anymore.)
I recently got my Ph.D. in Computer Science at Carnegie Mellon University, advised by Virginia Smith. Prior to CMU, I received undergraduate degrees in Computer Science and Economics from Peking University. I am currently working as a postdoctoral researcher at the Fundamental AI Research (FAIR) team at Meta.
My research generally centers around large-scale machine learning and optimization. Specific topics include:
Efficient distributed training with applications to federated/collaborative learning (FedProx, FedDANE, Ditto)
Risk-averse or risk-seeking learning with applications to fairness and robustness (q-FFL, TERM)
I am particularly interested in designing, analyzing, and evaluating principled learning algorithms, modeling practical assumptions (e.g., communication constraints and heterogeneity) to address the above issues, as well as their interplays.
Starting in Summer 2024, I will join the University of Chicago as an Assistant Professor in the Department of Computer Science and the Data Science Institute. If you are interested in working with me, please apply through the CS PhD program and/or the DS PhD program, and mention my name in your application(s). You are also welcome to drop me a note.