Welcome!

Hi! My name is Zhaolin, and I am a sixth year Ph.D. candidate in the School of Engineering and Applied Science at Harvard University. I am advised by Prof. Na (Lina) Li. Before starting my Ph.D., I earned both a B.S. degree in Mathematics (with Distinction) and a M.S. degree in Statistics at Stanford University.

My research interest lies in the theory and practice of model-free optimization as well as representation learning in reinforcement learning. I am interested in designing sample-efficient, scalable and provable optimization and control tools for challenging problems in applications such as bioengineering, networked control and fluid control, where data and knowledge about the existing environment may both be limited or expensive to acquire. In my research, I draw from tools in zeroth-order and Bayesian optimization, representation learning, and reinforcement learning, and actively collaborate across disciplines with researchers in other fields such as bioengineering and fluid control. For more details on my research projects and interests, please refer to the research and publication tabs.