<Yi Tian>

I am a Research Scientist at Meta, on the Business AI Agent team in Monetization GenAI. I received my Ph.D. in EECS from MIT, advised by Prof. Suvrit Sra, with a minor in mathematics. During my Ph.D., I was fortunate to also work with Prof. Russ Tedrake and Prof. Kaiqing Zhang. I received my B.E. in Automation from Tsinghua University, where I was fortunate to be advised by Prof. Jiwen Lu and Prof. Keyou You. My research interests lie broadly in generative AI, reinforcement learning, control theory, game theory, robotics, optimization, and their intersections.

Google Scholar LinkedIn Resume (ver: Sep 2025)

Research

Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control
Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra
62nd IEEE Conference on Decision and Control (CDC), 2023. [short] [long]

Convex and Non-Convex Optimization under Generalized Smoothness
Haochuan Li*, Jian Qian*, Yi Tian, Alexander Rakhlin, Ali Jadbabaie
37th Conference on Neural Information Processing Systems (NeurIPS), 2023. (Spotlight) [arXiv]

Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control?
Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra
5th Annual Learning for Dynamics & Control Conference (L4DC), 2023. (Oral) [arXiv]

Byzantine-Robust Federated Linear Bandits
Ali Jadbabaie, Haochuan Li, Jian Qian, Yi Tian
61st IEEE Conference on Decision and Control (CDC), 2022. [short] [long]

Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization
Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie
35th Conference on Neural Information Processing Systems (NeurIPS), 2021. [pdf] [arXiv]

Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra.
38th International Conference on Machine Learning (ICML), 2021. (Long talk) [pdf] [arXiv]

Online Learning in Unknown Markov Games
Yi Tian*, Yuanhao Wang*, Tiancheng Yu*, Suvrit Sra.
38th International Conference on Machine Learning (ICML), 2021. [pdf] [arXiv]

Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes
Yi Tian*, Jian Qian*, Suvrit Sra.
34th Conference on Neural Information Processing Systems (NeurIPS), 2020. (Spotlight) [pdf] [arXiv]

Towards Understanding the Trade-off Between Accuracy and Adversarial Robustness
Congyue Deng*, Yi Tian*.
International Conference on Machine Learning Workshop on Security and Privacy (ICMLW), 2019. [pdf]

Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition
Yansong Tang*, Yi Tian*, Peiyang Li, Jiwen Lu, Jie Zhou.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [pdf]

Action Recognition in RGB-D Egocentric Videos
Yansong Tang, Yi Tian, Jiwen Lu, Jianjiang Feng, Jie Zhou.
IEEE International Conference on Image Processing (ICIP), 2017. [pdf]