I am (starting in July 2022) a research scientist at Deepmind in London, UK working on applied reinforcement learning. My work aims to solve the research challenges associated with using RL to tackle real-world problems (e.g. sample efficiency, safety, structured state representations, etc.)
I recently graduated with a PhD from the Computer Science department at The University of Southern California, advised by Fei Sha. My work there was in deep (primarily multi-agent) reinforcement learning, and was motivated by solving complex cooperative tasks in which several forms of structure (sparse interactions, subtasks, etc.) exist. The goal of my thesis was to develop modeling strategies which leverage this structure to improve generalization as well as learning efficiency. I got my start in research working in a computational cognitive neuroscience lab run by John Pearson at Duke University, after completing my bachelor’s there.
In my free time I enjoy playing soccer and basketball, video games, cooking, reading, hiking, and watching my favorite sports teams (Duke Basketball, Michigan Football, Tottenham, US Soccer).