I am a final year PhD student in EECS at MIT. I am currently applying for faculty positions (Fall 2023). I am extremely fortunate to be advised by Caroline Uhler and David Sontag.

My long-term research is focused on rigorously applying machine learning and AI to accelerate scientific discovery, and to make robust predictions for interventions in complex systems. This involves developing methodology for causal structure learning, experimental design, and identifiable representation learning. In my PhD, I have focused on applying these methods in the context of cellular biology.

I’m a strong believer in the value of effective communication skills, and I’m a fellow in the EECS Communication Lab. Here are links to my slides and posters.

I take a lot of pride in mentoring and teaching, lecture notes and recordings from my 2023 course on causality can be found here.

I am the main developer of causaldag, a Python package for creating, manipulating, and learning causal graphical models.