I am a postdoctoral scholar in the Earth and Environmental Sciences Area at Lawrence Berkeley National Laboratory (LBNL). I completed my Ph.D. in Energy Resources Engineering at Stanford Doerr School of Sustainability from Stanford University in 2022, working with Prof. Louis J. Durlofsky. Prior to that, I graduated with honors from Tsinghua University, with a Bachelor’s degree in Environmental Engineering and a dual degree in Economics.

My research lies in the intersection of data assimilation, uncertainty quantification, scientific machine learning, and subsurface flow simulation. This includes applications in CO₂ geological storage, seawater intrusion, subsurface energy development, and battery modeling. I have developed approaches for inverse problems and uncertainty quantification in subsurface flow, energy storage, and environmental systems, using machine-learning and deep-learning techniques. My research goal is to develop computationally efficient, data-driven and physics-informed machine learning, data assimilation, and optimization methods for environmental and energy systems and for applications relevant to the energy transition and climate change.