James Stokes

James Stokes is an Assistant Research Scientist in the Department of Mathematics at the University of Michigan, affiliated with the College of Literature, Science, and the Arts. His research focuses on quantum algorithms, neural network quantum states, and their applications in theoretical physics and computational finance. Stokes holds a Ph.D. from the University of Pennsylvania (2015), along with M.Phil. and M.S. degrees from the University of Melbourne (2010) and a B.S. from the University of Sydney (2007).

His work bridges quantum computing and machine learning, addressing challenges in quantum chemistry simulation, partial differential equation solving, and gauge theory modeling. Recent articles highlight contributions to variational quantum algorithms, meta-variational Monte Carlo methods, and scalable architectures for quantum systems.

Stokes' research emphasizes algorithmic innovation in high-dimensional HJB equations, financial derivative pricing, and symmetry-preserving neural networks for gauge theories. His office is located in East Hall, Room 4079, and he can be reached via stokesjd@umich.edu.