Update: I will be starting as an Assitant Professor at Imperial College London in Janurary 2024, with a co-appointment from Earth Science Engineering and I-X (Imperial + AI). My group will focus 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. oppertunities in Fall 2024!
I am a Ph.D. candidate at the Energy Sciences & Engineering Department at Stanford Doerr School of Sustainability working with Professor Sally M. Benson. My research interest is in computational methods for earth sciences. I specialize in multiphase flow and transport for CO$_2$ geological storage, physics modeling, and machine learning.
I am currently 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. Stanford, I received my Bachelor’s degree with honors from Lassonde Mineral Engineering at University of Toronto and 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.