Azra Begzadić
Email: abegzadic (at) ucsd.edu
Azra Begzadić is a Ph.D. student in Mechanical and Aerospace Engineering at UCSD. Her research interests lie in safety-critical learning-based control.
Before joining UCSD, Azra received an M.Sc. from the Technical University in Munich, Germany, in 2023, and a B.Sc. from the Vienna University of Technology, Austria, in 2020 (both in electrical engineering and information technology).
In her free time, Azra enjoys photography, drawing, and reading books.
Selected Projects
Event-triggered learning for safe control: This framework uses event-triggered learning, which switches between prioritizing control performance and improving model accuracy based on the uncertainty of the learned model.
Safe reinforcement learning with reach-avoid safety filters: Using reach-avoid sets to minimally override the RL process while ensuring the system (a) maintains safety and (b) returns to its base configuration at the end of the horizon.
Related Papers
Azra Begzadić, Armin Lederer, Jorge Cortés, and Sylvia Herbert. “Learning high-order CBFs using Gaussian processes for systems in Brunovský canonical form.” Proceedings of the IEEE Conference on Decision and Control, Rio de Janeiro, Brazil, 2025, to appear.
Sander Tonkens*, Nikhil Uday Shinde*, Azra Begzadić*, Michael C Yip, Jorge Cortés, and Sylvia Herbert. “Space to Time: Out-of-Distribution Generalization of Safety Filters via Temporal Disturbance Encoding.” Second Workshop on Out-of-Distribution Generalization in Robotics at RSS, 2025.
Azra Begzadić*, Nikhil Uday Shinde*, Sander Tonkens*, Dylan Hirsch, Kaleb Ugalde, Michael C Yip, Jorge Cortés, and Sylvia Herbert. “Back to Base: Towards Hands-Off Learning via Safe Resets with Reach-Avoid Safety Filters.” Learning for Dynamics and Control (L4DC), 2025.
Armin Lederer*, Azra Begzadić*, Sandra Hirche, Jorge Cortés, Sylvia Herbert, "Safe Barrier-Constrained Control of Uncertain Systems via Event-triggered Learning", under review
Armin Lederer*, Azra Begzadić*, Neha Das, Sandra Hirche, "Safe Learning-Based Control of Elastic Joint Robots via Control Barrier Functions", 22nd IFAC World Congress 2023.
*co-first authors