I am a Research Scientist on the Adaptive Experimentation team. Prior to Meta, I completed my PhD in Statistics at Cornell University, and was also based at the University of California, San Francisco where I worked on interpretability techniques for healthcare applications. My current research focuses on causal inference and reinforcement learning, with a particular focus on developing safe and robust experimentation techniques. I am also interested in interpretability and algorithmic fairness.
Causal inference, interpretability, reinforcement learning, algorithmic fairness