John Schulman
John Schulman is a researcher known for work on reinforcement learning and training language models with human feedback. He coauthored Trust Region Policy Optimization in 2015 and Proximal Policy Optimization in 2017, two methods for updating a learning system's behavior. OpenAI's founding announcement names him among its original researchers, and He received his doctorate from Berkeley in 2016. He later contributed to InstructGPT and ChatGPT with large research and engineering teams. He was a Thinking Machines Lab cofounder and chief scientist in May 2025. In a September 2025 paper, he studied efficient model adaptation with LoRA.
- Now at
- Thinking Machines Lab
- Works
- 53
Publication numbers from OpenAlex, as of 14 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.
Timeline
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2015
Making learning updates more stable
Schulman and colleagues publish Trust Region Policy Optimization.
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2016
Completing a Berkeley doctorate
He received a doctorate in electrical engineering and computer sciences from Berkeley in 2016.
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2017
A more practical training method
With Filip Wolski, Prafulla Dhariwal, Alec Radford and Oleg Klimov, he publishes Proximal Policy Optimization.
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2022
Using feedback to follow instructions
Schulman co-authors the InstructGPT paper with Long Ouyang and a large team.
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May 2025
A new research setting
He was a Thinking Machines cofounder and chief scientist in May 2025.
Sources and credits
Photo: Eric Louis Haines, via Berkeley Engineering. License: Not stated by source. Source: engineering.berkeley.edu. Cropped to a square and resized. Ask us to remove or replace this photo.
- Schulman and colleagues: TRPO, February 2015
- OpenAI founding announcement, December 2015
- Berkeley Engineering: young innovators, June 2018
- Schulman and colleagues: PPO, July 2017
- Ouyang and colleagues: InstructGPT, March 2022
- OpenAI: ChatGPT launch, November 2022
- Berkeley: 2025 commencement program, page 19
- Schulman and Thinking Machines: LoRA Without Regret, September 2025