I study how machine learning can model and control physical systems.

I am a PhD student in Mechanical Engineering at the University of Washington, advised by Prof. Stefania Fresca and affiliated with the AI Institute in Dynamic Systems.

I develop neural surrogate models and reinforcement learning methods for high-dimensional flow control. My current work studies whether learned dynamics preserve the action sensitivities required for reliable controller extraction and optimization.

Before UW, I completed an MEng and BA in Information and Computer Engineering at the University of Cambridge. I studied nonlocal state inference in neural PDE surrogates and interpretable deep learning for wildfire prediction. I also completed research internships at the European Bioinformatics Institute and J.P. Morgan.

I enjoy moving between analysis, implementation, and physical validation. Outside research, I play badminton, hike, and explore the Pacific Northwest.