PeopleofSuperintelligence

Researcher

Benjamin Eysenbach

Benjamin Eysenbach is a Princeton computer scientist who studies reinforcement learning for AI agents that explore and learn skills. In 2019, he coauthored Diversity is All You Need and received a Hertz Fellowship as a first-year Ph.D. student at Carnegie Mellon. He later wrote about example-based reinforcement learning at Google Research, completed a machine learning Ph.D. in 2023, and joined Princeton Computer Science. His coauthored 1000 Layer Networks paper won the 2025 NeurIPS Best Paper Award, and he received a 2026 Sloan Research Fellowship; he is an assistant professor who runs Princeton's Reinforcement Learning Lab.

Badges

Timeline

  1. 2019

    DIAYN and a Hertz Fellowship

    In 2019, he coauthors Diversity is All You Need, a method for learning useful skills without a reward function. The Hertz Foundation names him a 2019 fellow while he is a first-year Ph.D. student in Carnegie Mellon University's Machine Learning Department.

  2. 2021

    Learning directly from examples

    At Google Research, he posts Recursive Classification in 2021, describing an example-based control method that learns directly from examples without defining a reward function.

  3. By 2023

    MIT and a Carnegie Mellon PhD

    He completes a machine learning Ph.D. at Carnegie Mellon in 2023. He holds an undergraduate degree in mathematics from MIT and works at Google Brain/Research before and during his doctoral work.

  4. 2023

    Assistant professor at Princeton

    He joins Princeton's faculty as an assistant professor of computer science in 2023.

  5. 2025

    A NeurIPS Best Paper Award

    His coauthored 1000 Layer Networks for Self-Supervised RL wins the NeurIPS 2025 Best Paper Award. Its experiments show that increasing depth up to 1,024 layers significantly improves performance in goal-conditioned self-supervised reinforcement learning.

  6. 2026

    A Sloan Research Fellowship

    He receives a 2026 Sloan Research Fellowship in computer science while serving as an assistant professor at Princeton.

  7. As of October 2026

    Leading Princeton's RL lab

    He is an assistant professor of computer science at Princeton and runs the Princeton Reinforcement Learning Lab. The group studies how AI systems can learn to explore the world and uncover skills or knowledge.

Career

  1. Since 2023Princeton UniversityAssistant Professor of Computer Science
  2. From 2021Google Research

Education

  1. 2023Carnegie Mellon UniversityPh.D. in machine learning
  2. Massachusetts Institute of TechnologyUndergraduate degree in mathematics

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Benjamin Eysenbach. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Benjamin Eysenbach. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  3. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes Princeton University. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Princeton University. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Diversity is All You Need: Learning Skills without a Reward Function research.google. Checked 20 October 2026.
  2. The Fannie and John Hertz Foundation Announces 2019 Graduate Fellows hertzfoundation.org. Checked 20 October 2026.
  3. Recursive Classification: Replacing Rewards with Examples in RL research.google. Checked 20 October 2026.
  4. Benjamin Eysenbach | Computer Science cs.princeton.edu. Checked 20 October 2026.
  5. NeurIPS 2025 Awards neurips.cc. Checked 20 October 2026.
  6. 1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities proceedings.neurips.cc. Checked 20 October 2026.
  7. Ben Eysenbach, expert in reinforcement learning, awarded 2026 Sloan Fellowship cs.princeton.edu. Checked 20 October 2026.
  8. Benjamin Eysenbach ben-eysenbach.github.io. Checked 20 October 2026.