My current research focuses on generative optimization and exploration — bridging decision-making under uncertainty (e.g., RL/Control, bandits), optimization (e.g., on probability spaces, submodular) and generative modeling (e.g., diffusion and flows) to tackle fundamental challenges in large-scale scientific discovery. I work on mathematical foundations, scalable learning methods, and real-world applications in chemistry and biology.
