Diederik Beckers

Diederik Beckers is a Resnick Postdoctoral Scholar in Aerospace at the California Institute of Technology (Caltech), advised by Jane Bae. His research focuses on advancing computational methods for unsteady aerodynamics, integrating deep reinforcement learning with fluid dynamics to address control challenges in disturbed environments. He specializes in developing fast aerodynamic models, gust interaction simulations, and computationally-augmented wind tunnel techniques. His work bridges theoretical fluid dynamics with practical applications in aircraft control and flow optimization.

Beckers' research interests emphasize model-based reinforcement learning for flow control, numerical methods for simulating irrotational gusts, and low-order aerodynamic modeling. His contributions include improving immersed boundary projection methods and advancing potential flow computations on Cartesian grids. He collaborates with the Bae group to explore experimental-computational hybrid systems for aerodynamic data assimilation.

His publications span topics like airfoil pitch control under freestream disturbances, wind tunnel effects on gust interactions, and fast computational models for real-time aerodynamic analysis. This body of work reflects a cohesive focus on merging machine learning with classical fluid mechanics to solve complex aerodynamic problems.