Ryne Beeson

Ryne Beeson is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at Princeton University. His research focuses on Control, Robotics and Dynamical Systems, with an emphasis on optimal control, nonlinear filtering, and trajectory optimization. His work applies to spacecraft guidance, navigation, and control, as well as space situational awareness. Beeson received his doctoral degree in Aerospace Engineering from the University of Illinois at Urbana-Champaign in 2020, following an M.S. in Mathematics and earlier degrees in Aerospace Engineering from Illinois. He has contributed to research on numerical optimization algorithms and spacecraft trajectory software.

Ryne Beeson is an Assistant Professor at Princeton University, specializing in Data Assimilation, Optimal Control, Dynamical Systems, Astrodynamics, and Space Domain Awareness. His research focuses on developing advanced methods for trajectory optimization, particularly using diffusion models and deep generative models to solve complex non-convex problems in aerospace systems. He also explores data-driven approaches for adaptive observations in multi-scale systems and the role of invariant manifolds in robust trajectory design. His work bridges theoretical and applied aspects of control theory and dynamical systems, with applications in autonomous systems and space mission design.