My research involves developing theoretical and computational methods for the predictive design and discovery of materials. A major focus of my work is the development of fully continuous, gradient-based approaches that accelerate first-principles computational materials discovery, with applications ranging from determining atomic structure from electron ptychography images to searching for novel stable high-(T_c) superconductors. I also develop polymer self-consistent field theory codes and apply density functional theory to predict the equilibrium morphologies of block copolymer melts given a chosen set of monomers. In parallel, I develop novel three-dimensional topology optimization methods and rigorous theoretical bounds for designing membrane architectures with enhanced conductivity and elastic response approaching fundamental limits. More broadly, my research also includes physics-inspired theoretical approaches to understanding deep learning systems.

• 2026 -- Webb@KIC Fellowship
• 2026 -- CABES Lena F. Kourkoutis Energy Research Fellowship
• 2024 -- Trevor R. Cuykendall Memorial Prize
• 2021 -- Colman Fellowship
• 2021 -- Best ECE Undergraduate Research Award
• 2021 -- Henry G. Booker Award

2021 --- BS in Engineering Physics from the University of California, San Diego