Neha Wadia

Reveal Contact Info

PhD Student


DeWeese Lab

Current Research

I am generally interested in the theoretical foundations of machine learning, and in the interface of computer science, high-dimensional statistics, and statistical mechanics. All my projects eventually distill down to the question of how to solve a specific optimization problem. Currently active projects include leveraging ideas from numerical integration to construct adaptive step size routines in gradient-based optimization, and developing perturbative solutions to the Fokker-Planck equation for a driven Brownian system.


I am a graduate student in the Biophysics Graduate Group, advised by Michael I. Jordan and Michael R. DeWeese. Before I came to Berkeley, I was a Junior Research Fellow at the National Center for Biological Sciences in Bangalore, India. Before that, I completed a Masters degree in theoretical physics at the Perimeter Institute for Theoretical Physics in Waterloo, Canada. I was an undergraduate at Amherst College, where I received a degree in physics.

To my surprise, it was my interest (early in graduate school) in neuroscience that eventually led me to do research in computer science and statistical physics.