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Pieter Abbeel

Professor, Jim Gray Chair of Engineering; Director of the Berkeley Robot Learning Lab; Co-Director of BAIR, UC Berkeley

Pieter Abbeel is a Professor at UC Berkeley, where Abbeel holds the Jim Gray Chair of Engineering, directs the Berkeley Robot Learning Lab and co-directs the Berkeley Artificial Intelligence Research (BAIR) lab; Abbeel has also been an Amazon Scholar since 2024. Abbeel's homepage lists earlier roles as a research scientist at OpenAI (2016–2017) and as co-founder, President and Chief Scientist of Covariant (2017–2024). Abbeel co-authored the Trust Region Policy Optimization paper and the Denoising Diffusion Probabilistic Models paper, and the homepage links Abbeel's CS294-158 Deep Unsupervised Learning course.123

At a glance

Current roles
Professor, Jim Gray Chair of Engineering; Director of the Berkeley Robot Learning Lab; Co-Director of BAIR +1 more
Sector
University
Education
Stanford, UC Berkeley
Work listed
2
Honors
8
Sources cited
5
Profile reviewed

Career

Pieter Abbeel's Berkeley EECS faculty page lists a 2008 PhD in computer science from Stanford University. At UC Berkeley, Abbeel is a Professor holding the Jim Gray Chair of Engineering, directs the Berkeley Robot Learning Lab and co-directs the BAIR lab.41

Outside the university, Abbeel co-founded Gradescope (2014–2018), was a research scientist at OpenAI (2016–2017) and an OpenAI advisor from 2015, and was co-founder, President and Chief Scientist of Covariant (2017–2024), a company working on AI for robotic automation. Abbeel has been an Amazon Scholar since 2024 and hosts The Robot Brains Podcast.14

Research

Abbeel's lab works on deep reinforcement learning, imitation learning, unsupervised learning, transfer learning and meta-learning, and studies how AI could advance other science and engineering fields. Earlier work with Adam Coates and Andrew Ng applied apprenticeship learning to autonomous helicopter aerobatics, and a 2010 ICRA paper on learning surgical tasks from human-guided demonstrations received a best medical robotics paper award.4

With collaborators, Abbeel co-authored Trust Region Policy Optimization (2015), a policy optimization method for neural network policies, and Denoising Diffusion Probabilistic Models (2020) with Jonathan Ho and Ajay Jain, which showed high-quality image synthesis with diffusion models.23

Teaching

Abbeel's courses include CS188 Introduction to Artificial Intelligence, CS287 Advanced Robotics, and CS294-158 Deep Unsupervised Learning, which was offered in Spring 2024. Abbeel also co-taught CS294-190 with Stuart Russell, presented an ICML 2021 tutorial on unsupervised reinforcement learning, and co-organized the Full Stack Deep Learning bootcamp.15

Work and contributions

  • Denoising Diffusion Probabilistic Models Published research

    Co-author with Jonathan Ho and Ajay Jain of the 2020 paper, which presents image synthesis with diffusion probabilistic models trained on a weighted variational bound.3

  • Trust Region Policy Optimization (TRPO) Published research

    Co-author with John Schulman, Sergey Levine, Philipp Moritz and Michael I. Jordan of the 2015 paper that describes the TRPO algorithm for optimizing neural-network policies.2

Timeline

  1. Completed a PhD in computer science at Stanford University.4
  2. Co-founded Gradescope, an AI tool to help teachers grade homework and exams.14
  3. Co-authored Trust Region Policy Optimization with John Schulman and colleagues.2
  4. Joined OpenAI as a research scientist, a role held until 2017.1
  5. Co-founded Covariant, serving as President and Chief Scientist until 2024.1
  6. Co-authored Denoising Diffusion Probabilistic Models with Jonathan Ho and Ajay Jain.3
  7. Became an Amazon Scholar.1

Other documented roles

Roles the sources document that are not confirmed as current.

  • Research Scientist (2016–2017), OpenAI1
  • Co-Founder, President, and Chief Scientist (2017–2024), Covariant1

Honors and recognition

  • IEEE Kiyo Tomiyasu Award · Institute of Electrical and Electronics Engineers, 20224
  • ACM Prize in Computing · Association for Computing Machinery, 20214
  • IEEE Fellow · Institute of Electrical and Electronics Engineers, 20184
  • Diane S. McEntyre Award for Excellence in Teaching Computer Science · UC Berkeley EECS, 20184
  • CRA-E Undergraduate Research Faculty Mentoring Award · Computing Research Association, 20164
  • Presidential Early Career Award for Scientists and Engineers · U.S. Department of Defense, 20134
  • DARPA Young Faculty Award · Defense Advanced Research Projects Agency, 20134
  • RAS Early Career Award · IEEE Robotics and Automation Society, 20124

Where they work

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References

5 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026

  1. Pieter Abbeel — homepage (Current Positions)Pieter Abbeel (UC Berkeley EECS) · Official page · accessed Oct 21, 2026
  2. Trust Region Policy Optimization (arXiv 1502.05477)arXiv · Paper · published Feb 19, 2015 · accessed Oct 21, 2026
  3. Denoising Diffusion Probabilistic Models (arXiv 2006.11239)arXiv · Paper · published Jun 19, 2020 · accessed Oct 21, 2026
  4. Pieter Abbeel — EECS at UC Berkeley faculty pageUC Berkeley EECS · Official page · accessed Oct 21, 2026
  5. CS294-158-SP24 Deep Unsupervised Learning, Spring 2024UC Berkeley (course site) · Official page · accessed Oct 21, 2026