Jean Oh

Associate Research Professor Carnegie Mellon University

  • Pittsburgh PA

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Biography

Jean Oh is an Associate Research Professor at the Robotics Institute at Carnegie Mellon University (CMU) and head of the roBot Intelligence Group (BIG). Jean's research focuses on building Creative Physical AI technologies that remind us of "what makes us human," promoting human values such as safety, creativity, and compassion across diverse domains including self-driving vehicles, safe aviation, and arts. Jean's work on social robot navigation and creative robotics has won several best paper awards at major robotics conferences including ICRA and IROS, and has been featured in media worldwide including New York Times and the Telegraph. Jean has been leading a series of interdisciplinary events on AI/Robotics and Arts at Humanoids'25, ICRA'25, NeurIPS'24, NeurIPS'23, RSS'21, SIGGRAPH'21 and CVPR'21. Jean is currently Co-Chair of the IEEE RAS Technical Committee on Cognitive Robotics.

Currently, I am leading the perception and the learning tasks for the DARPA Aircrew-Labor In-Cockpit Automation System (ALIAS) program (co-PI) that aims to bring intelligence to cockpits through semantic perception and learning new skills from observing experienced pilots. I am also a PI on the intelligence architecture subtask of the ARL RCTA program where my team’s work on language understanding on robot navigation won the Best Cognitive Robotics Paper Award at the IEEE International Conference on Robotics and Automation (ICRA) in 2015. My newest project is the US DoD – Korea MOTIE (co-PI) collaboration on robotics technologies for disaster response, where I will be leading the semantic map construction by leveraging text data from social media and crowdsourcing.

Areas of Expertise

Field and Service Robotics
Human Robot Collaboration
Robotics Foundations
Social Robots
Motion
Human-Centered Robotics
AI Reasoning for Robotics

Social

Education

Yonsei University

B.S.

Biotechnology

Columbia University

M.S.

Computer Science

Carnegie Mellon University

Ph.D.

Language and Information Technologies

Patents

Vehicle operator workload estimation system and method

12504820

2025-12-23

An estimation system includes a plurality of sensors that generate a multimodal signal, where the multimodal signal indicates a state of a user. The estimation system also includes at least one processor that receives the multimodal signal from the plurality of sensors, and determines a workload experienced by the user based on the multimodal signal and a workload model, wherein the workload model relates multimodal signal data to an experienced workload.

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Articles

Safety Not Found (404): Hidden Risks of LLM-Based Robotics Decision Making

arXiv

J Han, J Seo, J Min, J Oh, J Kim

2026-01-09

One mistake by an AI system in a safety-critical setting can cost lives. As Large Language Models (LLMs) become integral to robotics decision-making, the physical dimension of risk grows; a single wrong instruction can directly endanger human safety. This paper addresses the urgent need to systematically evaluate LLM performance in scenarios where even minor errors are catastrophic.

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InterPReT: Interactive Policy Restructuring and Training Enable Effective Imitation Learning from Laypersons

arXiv

FG Zhu, J Oh, R Simmons

2026-02-04

Imitation learning has shown success in many tasks by learning from expert demonstrations. However, most existing work relies on large-scale demonstrations from technical professionals and close monitoring of the training process.

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Jean Oh

Google Scholar

Full publication list: https://scholar.google.com/citations?hl=en&user=jizMCFAAAAAJ&view_op=list_works&sortby=pubdate