Udaya Ghai

I am a Senior Machine Learning Scientist at Amazon, where my research focuses on applying reinforcement learning to supply chain optimization. More boradly, I'm interested in theory and algorithms for machine learning, particularly reinforcement learning, control, optimization (convex and non-convex), and online learning.

I completed my Ph.D. in Computer Science at Princeton under the supervision of Prof. Elad Hazan, where we worked at the intersection of online learning and control theory. I also spent time as a student researcher at Google Brain. In a previous life, I was a sofware engineer at IMC Trading after completing a B.S. in Computer Science at Caltech.


With Arushi Gupta, Wenhan Xia, Karan Singh, Elad Hazan.
Non-convex online learning via algorithmic equivalence. NeurIPS 2022 and Continuous Time Methods Workshop @ ICML 2022.
With Zhou Lu and Elad Hazan.
A Regret Minimization Approach to Multi-Agent Control. ICML 2022 and GMAS Workshop @ ICLR 2022 (Oral Presentation + Best Poster).
With Udari Madhushani, Naomi Leonard, and Elad Hazan.
Robust Online Control with Model Misspecification. L4DC 2022 and RL Theory Workshop @ ICML 2021.
With Xinyi Chen, Elad Hazan, and Alexandre Megretski.
With Daniel Suo, Edgar Minasyan, Paula Gradu, Xinyi Chen, Naman Agarwal, Cyril Zhang, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel Cohen, and Elad Hazan.
With David Snyder, Anirudha Majumdar, and Elad Hazan.
With Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Karan Singh, Cyril Zhang, Anirudha Majumdar, and Elad Hazan.
With Holden Lee, Karan Singh, Cyril Zhang, and Yi Zhang.
With Elad Hazan and Yoram Singer.