Andrea Bajcsy
Intent Lab Research Publications Teaching Contact

I am an Assistant Professor in the Robotics Institute and School of Computer Science at Carnegie Mellon University.

I lead the Interactive and Trustworthy Robotics Lab (Intent Lab). We study how to make learning-enabled robots safely and intelligently interact with humans. We draw upon methods from optimal control, dynamic game theory, Bayesian inference, and deep learning.

I obtained my Ph.D. in electrical engineering & computer science at UC Berkeley with Anca Dragan and Claire Tomlin. Previously, I was also a postdoctoral scholar with Jitendra Malik and worked at NVIDIA in the Autonomous Vehicle Research Group.

Prospective students: please see here.

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Unsure how to pronounce my last name? Bajcsy sounds like BYE-chee.


  • [Apr 2024]

    I'm thrilled to receive the Google Research Scholar Award!
  • [Mar 2024]

    New arXiv paper on a general calibrated regret metric for detecting and mitigating human-robot interaction failures; check out the applicability to anomaly detection in interactive generative planners too!
  • [Feb 2024]

    New arXiv paper on intent demonstration in general-sum dynamic games.
  • [Jan 2024]

    Our work on visual representation alignment for robot learning was accepted to ICLR 2024! Check out the new results in the arXiv version.
  • [Jan 2024]

    Our work on contingency games was accepted to RA-L 2024!
  • [Jan 2024]

    Our work on stabilized and robust online learning from humans was accepted to RA-L 2024!
  • [Dec 2023]

    New pre-print on Adaptive Human Trajectory Prediction via Latent Corridors.
  • [Oct 2023]

    Submitted a paper to ICLR! We propose Representation-Aligned Preference-based Learning (RAPL), a tractable video-only method for solving the visual representation alignment problem and learning visual robot rewards via optimal transport.