Jason Bramburger

Jason Bramburger is an Assistant Professor at Concordia University and an adjunct professor at McGill University. He is a member of the CRM Applied Math Lab and contributes to the Physica D Editorial Board. His research focuses on dynamical systems, data-driven discovery, pattern formation, and polynomial optimization applied to differential equations. He holds a Ph.D. from the University of Ottawa (2017), with postdoctoral fellowships at Brown University and the University of Victoria, and prior experience as an acting instructor at the University of Washington.

Research interests include multiscale dynamics, nonlinear Floquet theory, and Koopman operator methods. Recent work emphasizes data-driven analysis of dynamical systems, with applications to Poincaré maps, invariant measures, and control systems. Key contributions include methods for discovering Poincaré maps via sparse regression and bounding long-term system behaviors using convex optimization.

Notable publications span topics like real-time motion detection, localized patterns in networks, and ergodic optimization. Bramburger actively contributes to open-source projects, including a textbook on Data-Driven Methods for Dynamic Systems, and maintains GitHub repositories for computational tools in dynamical systems and neural networks.