Grant joined the plasma physics Ph.D. program in 2023. He earned a B.A. in Molecular Biology & Biochemistry from Wesleyan University in 2019, specializing in computational biophysics and protein dynamics. After tutoring for a year in Austin, Texas, he ventured back to the East Coast to obtain an M.S. in Biomedical Engineering from Columbia University in 2022, where he researched the computational genomics of brain cancer. He spent the next year in the plasma physics Ph.D. program at the University of Wisconsin-Madison. There, he wrote numerical algorithms for magnetohydrodynamic equilibrium calculations in tokamaks and explored the possibility of using physics-informed neural networks to solve partial differential equations in stellarators.
Advisor: Steve Sabbagh
Research Focus: interpretability in physics-guided machine learning for understanding and predicting plasma disruption event chains in tokamaks and signaling their avoidance and mitigation.