About me
I am a Postdoctoral Research Fellow at Mitsubishi Electric Research Laboratories, and a Research Affiliate at MIT in the Aerospace Controls Laboratory.
I am interested in developing reliable, data-driven algorithms for decision making and control. In order to trust that data-driven methods will deliver reliable performance in complex real-world applications, my research focuses on the need for robustness, safety, and generalization. I primarily explore these topics in the context of deep reinforcement learning, imitation learning, and self-supervised learning, with applications in robotics.
I received my PhD in systems engineering from Boston University, where I was advised by Yannis Paschalidis and Christos Cassandras. I also hold a MS in systems engineering from Boston University, and a BA in mathematics and mathematical economics from Colgate University.
Selected News
| Jan 2025 | Our paper on physics-informed evidential traversability learning was published in IEEE RA-L. |
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| Jan 2025 | Our paper on visually robust imitation learning from videos was accepted to ICRA 2025. |
| Dec 2024 | New paper on robust dynamics generalization in deep RL is now available on arXiv. |
| Mar 2024 | Our paper on optimal transport perturbations for robust and safe RL was published in TMLR. |
| Dec 2023 | Our paper on risk-averse model uncertainty for safe RL appeared at NeurIPS 2023. |
| Aug 2023 | I started as a Postdoctoral Research Fellow at Mitsubishi Electric Research Laboratories, and a Research Affiliate at MIT in the Aerospace Controls Laboratory. |
| Aug 2023 | I received my PhD in systems engineering from Boston University after successfully defending my dissertation on reliable deep reinforcement learning. |
Selected Publications
Check out the Publications page for a full list of my publications.