Astghik Hakobyan wins the best ECE M.S. thesis award. Her thesis, entitled “Risk-Aware Distributionally Robust Optimization for Learning-Based Autonomous Systems,” has been evaluated as “excellent, very creative research that draws upon concepts from mathematical finance (conditional value-at-risk), machine learning (Wasserstein metric, Gaussian process regression), and control (model predictive control) to address the practical and challenging problem of robot motion planning in dynamic unstructured environments.”

Congratulations, Astghik!