Update: I will be starting as an assistant professor at Imperial College London in January 2024, with a co-appointment from Earth Science Engineering and I-X (Imperial + AI). My group focuses on AI for Energy Transition, with special emphasis on subsurface energy storage and CO$_2$ geological storage. Please reach out if you are interested in Ph.D. opportunity in Fall 2024!

My research interest is in computational methods for earth sciences, with a special emphasis on multiphase flow and transport for CO$_2$ geological storage, physics modeling, and machine learning. I obtained my Ph.D. from the Energy Sciences & Engineering Department at Stanford Doerr School of Sustainability working with Professor Sally M. Benson. I was an ExxonMobil Emerging Energy Fellow through the Stanford Strategic Energy Alliance.

I received my Master’s degree in Fluid Mechanics and Hydrology from Civil and Environmental Engineering at Stanford University. Prior to my Ph.D. at Stanford, I received my Bachelor’s degree with honors from Lassonde Mineral Engineering at the University of Toronto and was nominated as 16 Grads to Watch.

Check out ccsnet.ai, a machine learning-based web application for real-time CO$_2$ plume migration and pressure buildup prediction. This web application provides 1,000 predictions per day to researchers, students, regulators, and industrial users across the world.