Publications include 'Optimism Without Regularization: Constant Regret in Zero-Sum Games' (NeurIPS 2025); 'Fast and Furious Symmetric Learning in Zero-Sum Games: Gradient Descent as Fictitious Play' (COLT 2025), among others. Preprints: 'Online Multi-Agent Control with Adversarial Disturbances' (May 2025); 'Optimistic Online Learning in Symmetric Cone Games' (March 2025).
Research Experience
Started as a postdoctoral research fellow at SUTD in Singapore in September 2024, working with Georgios Piliouras and Antonios Varvitsiotis; interned with the privacy-preserving machine learning research group at Meta in NYC during Summer 2022, collaborating with Sen Yuan and Huanyu Zhang.
Education
Received a PhD in Computer Science from Yale University in May 2024, advised by James Aspnes; visited IST Austria in 2023 and summer 2024, hosted by Dan Alistarh and Krish Chatterjee.
Background
Research interests lie at the intersection of theoretical computer science and machine learning, including online learning, game theory, optimization, bandits/decision making, distributed algorithms, opinion dynamics, and computation in multi-agent settings.
Miscellany
Co-designed and co-instructed a new graduate-level course on 'Online Learning and Learning in Games' at SUTD.