• Artificial Intelligence, data science, and machine learning
• Geoenergy and subsurface flow
• Surrogate modelling
• Data assimilation and uncertainty quantification

Before joining Heriot-Watt, I was a Postdoctoral Scholar in the Department of Energy Science and Engineering at Stanford University. I earned my PhD in Energy and Resources Engineering from Peking University, and my Bachelor’s degree in Petroleum Engineering from the China University of Petroleum (Beijing).

My research focuses on sustainable geoenergy development and subsurface resource management, with particular emphasis on uncertainty quantification, data assimilation, and decision-making for subsurface flow systems. Key application areas include geological carbon storage, geothermal energy extraction, hydrocarbon production, and water resource management. My work integrates AI models, numerical simulations, probabilistic algorithms and multi-source data to advance intelligent, safe, and efficient subsurface energy and resource management practices, contributing to a more sustainable and secure energy future.