Publications
Rohit Sonker, Hiro Farre, Jiayu Chen, Andrew Rothstein, Ian Char, Ricardo Shousha, Egemen Kolemen, Jeff Schneider, “Offline Reinforcement Learning for Rotation Profile Control in Tokamaks”, Learning for Dynamics & Control Conference (L4DC), 2026.
Tejus Gupta, Rohit Sonker, EM Karagözlü, Barnabás Póczos, Jeff Schneider, “Large Language Model-based Bayesian Optimization for Tokamak Stabilization”, Workshop on Machine Learning and Physical Sciences, NeurIPS 2025.
Rohit Sonker*, Alexandre Capone*, Andrew Rothstein, Hiro Farre, Egemen Kolemen, Jeff Schneider, “Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks”, International Conference on Machine Learning (ICML), 2025.
* Equal contribution
Andy Rothstein, Hiro Farre, Rohit Sonker, SangKyeun Kim, Azarakhsh Jalalvand, Jeff Schneider, Egemen Kolemen, “Preemptive tearing mode suppression using real-time ECH steering machine learning stability predictions on DIII-D”, Bulletin of the American Physical Society, 2024
Vaisakh Shaj, Dieter Büchler, Rohit Sonker, Philipp Becker, Gerhard Neumann, “Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios”, International Conference on Learning Representations (ICLR), 2022
R. Sonker and A. Dutta, “Adding Terrain Height to Improve Model Learning for Path Tracking on Uneven Terrain by a Four Wheel Robot”, IEEE Robotics and Automation Letters, 2021
Rohit Sonker, Ayush Mishra, Palvika Bansal, Anup Pattnaik, “Techniques for Medical Concept Identification from Multi-Modal Images”, CEUR Workshop Proceedings, CLEF 2020 (Oral)