Oleh /Oleg/ Rybkin

Hi! I am Oleg, a reinforcement learning researcher at Cursor.

I am interested in learning generalizable intelligence by large-scale RL.

I received my Ph.D. from University of Pennsylvania, where I worked with Kostas Daniilidis and Sergey Levine, and did a postdoc at UC Berkeley with Pieter Abbeel and Sergey Levine. I also went to Czech Technical University in Prague, and spent time at INRIA, TiTech, Google Brain, DeepMind, and xAI.

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News
  • Sep 2025: Preston wrote a blog post describing our findings in scaling laws for value-based RL.
  • Sep 2025: A follow-up paper on compute-optimal for value-based RL is accepted to NeurIPS.
  • May 2025: New paper on scaling laws for value-based RL is accepted to ICML!
  • May 2025: New paper on latent diffusion planning to appear at ICML as a spotlight.
  • Feb 2025: New preprint converting videos to tasks is out.
    • Publications (Highlighted / All)
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    Science reading list
    This is a list some books and shorter papers that changed my understanding of the field of AI and science in general. I hope you might find this useful too! The list is evolving, and suggestions for new reading material are welcome.

    Books:
    The Structure of Scientific Revolutions, Thomas S. Kuhn.
    Vision, David C. Marr.

    Short works:
    Computing Machinery and Intelligence, Alan M. Turing.
    The importance of stupidity in scientific research, Martin A. Schwartz.
    You and Your Research, Richard W. Hamming.
    As we may think, Vannevar Bush.
    Levels of Analysis for Machine Learning, Jessica Hamrick, Shakir Mohamed.
    How to Do Great Work, Paul Graham.
    Collaborators and Students
    Current:
    Past (current affiliation):
    Inspired by this template.