I am a postdoctoral scholar in the department of Energy Science and Engineering at Stanford Doerr School of Sustainability. I received my Ph.D. in Energy Resources Engineering from Stanford University in 2022, working with Prof. Louis J. Durlofsky. Before joining Stanford, I graduated with honors from Tsinghua University, with a Bachelor’s degree in Environmental Engineering and a dual degree in Economics.

My reseach lies in the intersection of data assimilation, scientific machine learning, decision making under uncertainty, subsurface energy development, CO₂ geological storage and environmental problems. I have developed approaches for inverse problems and uncertainty quantification for 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 techniques for environmental systems and for applications relevant to the energy transition and climate change.