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 enable robots to safely interact with the "open world". We broadly draw upon methods from optimal control, dynamic game theory, uncertainty quantification, 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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  [May 2025]

  Check out the Robotics Institute's article about my CAREER award and our initial results.
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  [May 2025]

  New paper on arXiv on uncertainty-aware latent safety filters which proactively steer robots away from both known and out-of-distribution failures.
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  [May 2025]

  We ran a successful 2nd edition of the Northeast Systems and Control Workshop!
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  [April 2025]

  Honored to receive the NSF CAREER Award!
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  [April 2025]

  Two papers accepted at RSS! Check them out here and here.

• [March 2025]

  Check out my talk titled "Towards Open World Robot Safety" at the RI Seminar!

• [Feb 2025]

  Two new arXiv papers: latent-space reachability for generalizing safety beyond collision-avoidance and VLM-in-the-loop policy steering!

• [Jan 2025]

  Two accepted papers (updating safety via language and safely influencing) at ICRA 2025!

• [Jan 2025]

  One accepted paper on conformalized IL at ICLR 2025!

• [Jan 2025]

  We are running two workshops at ICRA! One on Safely Leveraging VLMs in Robotics and the other on Public Trust in Autonomy

• [Oct 2024]

  New arXiv paper on conformal prediction + interactive imitation learning.

• [Sept 2024]

  Three new arXiv papers! Check out our work on robots that suggest safe alternatives, updating robot safety representations online from natural language, and robots that learn to safely influence.

• [Sept 2024]

  New paper accepted to CoRL on how not all prediction errors are made equal from the perspective of closed-loop robot performance.

[Older News]

[Aug 2024]

New paper at ECCV on adapting human trajectory predictors to scene-specific behaviors.

[June 2024]

New arXiv paper on human--AI safety through the lens of generative AI and control systems.

[Apr 2024]

New paper at RSS on using conformal prediction to calibrated shared controllers.

[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.

[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.

[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.