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Research Project

Distributionally Robust Optimization

This project addresses decision-making under uncertainty where the probability distribution of the uncertain parameter is unknown. Our research develops algorithms that ensure reliability and robustness against distribution shifts in real-world applications.

Publications

• Towards Resilient Tracking in Autonomous Vehicles: A Distributionally Robust Input and State Estimation Approach

  Kasra Azizi, Kumar Anurag, and Wenbin Wan

  IFAC Intelligent Autonomous Vehicles (IAV), 2025

  DOISlides