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.

email   |   cv   |   google scholar   |   github  |   bio

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

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  [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.
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  [Sep 2023]

  Submitted a paper to ICRA! We present Conformal Decision Theory, a new theoretical and algorithmic framework for online calibration of decision risk.

• [Aug 2023]

  ArXiv paper on learning vision-based pursuit-evasion robot policies. Check out our project website for videos of human-robot and robot-robot interaction ``in the wild''.

• [Aug 2023]

  1 paper accepted to CoRL! This work synthesizes safe control policies that explicitly account a robot's ability to learn and adapt at runtime.

• [Aug 2023]

  Submitted a paper to RA-L on stabilized and robust online learning from humans.

• [Aug 2023]

  Extended results on contingency games now on arXiv.

• [Aug 2023]

  I gave a talk at Bosch research.

• [Apr 2023]

  New paper on contingency games: a model for strategic interactions which allows a robot to consider the full distribution of other agents’ intents while anticipating intent certainty in the near future.

[Older News]

[Feb 2023]

I gave a talk at the Illinois Robotics Seminar at UIUC.

[Feb 2023]

I gave a talk at the Wisconsin Robotics Seminar Series at the University of Wisconsin-Madison.

[Jan 2023]

Our paper on long-term robot influence on humans got accepted to ICRA 2023!

[Jan 2023]

Our paper on modeling & influencing the dynamics of human learning was accepted to HRI 2023!

[Dec 2022]

I am on the organizing committee of RSS 2023.

[Dec 2022]

I gave a guest lecture at Princeton's Safety-Critical Robotic Systems class.

[Nov 2022]

I am serving as an Area Chair for L4DC.

[Oct 2022]

I gave an invited talk at Nuro on practical safety for human-robot interaction.

[Sept 2022]

Paper submitted to ICRA on robots that influence humans over long-term interaction.

[Sept 2022]

I'm serving as Associate Editor for ICRA 2023.

[Aug 2022]

I completed my PhD and started my postdoc! My thesis entitled "Bridging Safety and Learning in Human-Robot Interaction" can be found here.

[July 2022]

I gave an invited talk at the ICML Workshop on Safe Learning for Autonomous Driving (SL4AD).

[June 2022]

I gave an invited talk at the RSS Workshop on Close Proximity Human-Robot Collaboration.

[May 2022]

I accepted an offer to join the Robotics Institute in the School of Computer Science at Carnegie Mellon University (CMU) starting Fall 2023!

[Mar 2022]

Our paper Safety Assurances for Human-Robot Interaction via Confidence-aware Game-theoretic Human Models was accepted to ICRA 2022!

[Nov 2021]

I gave a talk at the University of Washington's Robotics Colloqium.

[Oct 2021]

Paper published in IJRR! In this work we formalize how physical human interaction with a robot can be treated as a form of communication, enabling robots to learn objectives from human corrections.

[Oct 2021]

New paper on arXiv! In this work we propose that robots use confidence-aware game-theoretic models of human behavior when assessing the safety of a human-robot interaction.

[Aug 2021]

I am grateful to have been selected for the Rising Stars Academic Career Workshop in EECS.

[Aug 2021]

New paper on arXiv! In this work we advocate for the use of Hamilton Jacobi (HJ) reachability as a unifying mathematical framework for comparing existing safety concepts used throughout industry and academia, and propose ways to expand its modeling premises in a data-driven fashion.

[April 2021]

I'm excited to join NVIDIA for an internship in the Autonomous Driving Research group led by Marco Pavone.

[Mar 2021]

Our paper on analyzing human models that adapt online was accepted to ICRA 2021!

[Feb 2021]

I gave a talk at University of Pennsylvania on analyzing human models that adapt online.

[Dec 2020]

I gave a talk on safe robots which learn from (and about) humans at the University of Chicago Laboratory School for the middle and high-school robotics club.

[Dec 2020]

I gave a talk at ETH Zurich on introspective human motion prediction for safe robot autonomy.