Nandan Tumu
PhD Student @ UPenn
I am a 5th-year PhD student at the University of Pennsylvania, passionate about advancing the frontiers of machine learning and robotics. My research spans three key areas: uncertainty quantification using Conformal Prediction, physics-informed machine learning, and the application of these techniques to multi-agent robotics and game environments. By integrating these approaches, I aim to develop learning methodologies for robotics which are more trustworthy, and have lower sample complexity. I am fortunate to be supported by the NSF Graduate Research Fellowship.
news
Jul 2024 | Our paper on conformal off-policy prediction was accepted to CDC 2024! |
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Mar 2024 | Our paper on designing practical non-conformity scores for planning and control was accepted to L4DC 2024! |
Mar 2023 | Our paper on Physics-constrained learning for trajectory prediction with Conformal Preduction was accepted to Intelligent Vehicles 2023! |
Jan 2022 | We won the Japan Automotive AI Challenge, against teams from Honda, Nissan, Toyota, and more! |