Viraj Mehta


I recently completed a Ph.D. at the Robotics Institute at Carnegie Mellon University advised by Jeff Schneider. As a researcher, I am broadly interested in reinforcement learning, generative models, and dynamical systems. In particular I work on solving control problems in science with machine learning in regimes where the data-generating process is expensive. Much of my work is motivated by the problem of plasma control for nuclear fusion; the various difficulties we face there frequently inspire more general machine learning problems we can solve as computer scientists. More recently, I’ve applied similar techniques to improve the efficiency of the alignment of language models.

Prior to my time at CMU, I spent time at KKR helping jumpstart their efforts with alternative data and analytics and at Hum Capital (formerly Capital Technologies) doing initial work on automating parts of capital allocation in private finance.

I completed a B.S. in Mathematics and an M.S. in Computer Science at Stanford University, where I conducted research on 3D vision and robot learning advised by Silvio Savaerese.

I’m from Austin, Texas, live in NYC, and bounce around between there, the Bay Area, and Tahoe. Outside of work, I spend my time flying airplanes, lifting weights, reading, and skiing.

selected publications

  1. Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction
    Viraj Mehta, Ian Char , Willie Neiswanger , and 5 more authors
    In IEEE Conference on Decision and Control , 2021
  2. Representational aspects of depth and conditioning in normalizing flows
    Frederic Koehler , Viraj Mehta, and Andrej Risteski
    In International Conference on Machine Learning , 2021
  3. An Experimental Design Perspective on Model-Based Reinforcement Learning
    Viraj Mehta, Biswajit Paria , Jeff Schneider , and 2 more authors
    In International Conference on Learning Representations , 2022
  4. Near-optimal Policy Identification in Active Reinforcement Learning
    Xiang Li* , Viraj Mehta*, Johannes Kirschner* , and 5 more authors
    In International Conference on Learning Representations (oral, top 5% of accepted papers) , 2023
  5. Exploration via Planning for Information about the Optimal Trajectory
    Viraj Mehta, Ian Char , Joseph Abbate , and 5 more authors
    In Advances in Neural Information Processing Systems , 2022
  6. Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration
    Viraj Mehta, Vikramjeet Das , Ojash Neopane , and 4 more authors
    arXiv preprint arXiv:2312.00267, 2023
  7. Automated experimental design of safe rampdowns via probabilistic machine learning
    Viraj Mehta, Jayson L Barr , Joseph Abbate , and 5 more authors
    Nuclear Fusion, 2024