معرفی
Jack Umenberger is a Senior Research Fellow at the University of Oxford’s Department of Engineering Science and the ZERO Institute for zero-carbon energy research. He joined Oxford in 2023 as a Departmental Lecturer within the Control Group. Previously, he held postdoctoral positions at MIT (2019-2022) and Uppsala University, Sweden (2017-2019), and earned his PhD from the University of Sydney in 2018 for work on data-driven modeling of dynamical systems.
His research focuses on the intersection of control theory, optimization, and machine learning, with applications to energy systems (e.g., battery management with Eatron Technologies) and robotics (e.g., motion planning with Dexai Robotics). Key areas of interest include data-driven system identification, model predictive control, reinforcement learning, and stability guarantees in dynamical systems.
Notable projects include work on shortest paths in graphs of convex sets for robotic motion planning, convergence analysis of direct policy search in reinforcement learning, and system identification with stability guarantees. His contributions emphasize blending discrete and continuous decision-making frameworks in optimization and control problems.
Umenberger collaborates with industry partners like Eatron Technologies and Dexai Robotics, advancing applications in energy and robotics. His work often bridges theoretical advancements with practical implementations, reflecting a commitment to impactful engineering solutions.
