PeopleofSuperintelligence

Researcher

Daniel Selsam

Daniel Selsam is an AI researcher whose work spans probabilistic programming, formal mathematics, neural reasoning, and language models. His career moves from probabilistic programming at MIT and Lean development at Microsoft Research to a 2019 Stanford PhD on neural networks and satisfiability. At OpenAI, he coauthors technical reports on GPT-4 and o1 and leads an Agents team whose work becomes part of o1. As of October 2026, he works on chain-of-thought optimization and data-efficient pretraining at OpenAI.

Now at
OpenAI
Works
19
Citations
3,347
h-index
9
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2014

    Probabilistic programming at MIT

    His early work at MIT explores probabilistic programming; in 2014, he coauthors Venture, an interactive virtual machine for probabilistic programming.

  2. 2017

    Lean and formal mathematics

    At Microsoft Research, he helps develop the Lean theorem prover; in 2017, he coauthors Developing Bug-Free Machine Learning Systems with Formal Mathematics.

  3. 2019

    A Stanford PhD on NeuroSAT

    For his Stanford computer science PhD, completed in 2019, he coauthors NeuroSAT, a message-passing network trained to predict satisfiability and solve SAT problems.

  4. 2023

    The GPT-4 technical report

    He coauthors OpenAI's GPT-4 technical report in 2023.

  5. 2024

    The o1 system card

    He coauthors OpenAI's o1 System Card in 2024.

  6. By 2025

    OpenAI's Agents team

    After OpenAI's 2023 Strawberry breakthrough, he leads an Agents team whose work joins the o1 project by 2025. In 2025, he coauthors a study comparing o1 with an early o3 checkpoint.

  7. As of October 2026

    OpenAI language-model research

    In October 2026, he works at OpenAI on chain-of-thought optimization for language models and data-efficient pretraining.

Career

  1. NowOpenAIAgents team lead
  2. 2018–2021Microsoft
  3. From 2017Microsoft Research
  4. From 2014Massachusetts Institute of Technology

Education

  1. 2019Stanford UniversityPhD

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. GPT-4 Technical Report2023 · 2,391 citations
  2. Data Programming: Creating Large Training Sets, Quickly2016 · 384 citationsWith Christopher De Sa and Christopher Ré
  3. Learning a SAT Solver from Single-Bit Supervision2018 · 213 citationsWith Leo de Moura
  4. Guiding High-Performance SAT Solvers with Unsat-Core Predictions2019 · Lecture notes in computer science · 76 citations
  5. OpenAI o1 System Card2024 · 48 citationsWith Adam Tauman Kalai, Ahmed El-Kishky and Boaz Barak

From OpenAlex, as of 19 October 2026.

  1. 13 of 79 people shaping AI with a former OpenAI role now work at AnthropicIncludes Daniel Selsam. Our estimates of where OpenAI recruits came from and where people with former OpenAI roles work now.
  2. The median h-index is 53 at universities and 19 at frontier AI labsIncludes Daniel Selsam. The median h-index is 53 at universities and 19 at frontier AI labs. We compare publishing careers, citations and moves to estimate how universities and frontier labs contribute to AI research.
  3. Google alumni founded or led 87 other organizations, the most among the labs we compareIncludes Daniel Selsam. We trace 212 organizations founded or led by AI lab alumni, and 223 career moves between the labs.
  4. 44% of AI career moves go from one university to anotherIncludes OpenAI. We estimate how 14,272 AI career moves link universities, companies, labs and government research centers, with net flows and the most common paths.

Colleagues

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

Sources and credits

Photo: We have no published photo of Daniel Selsam yet. Send us a free-licensed photo.

  1. Venture: a higher-order probabilistic programming platform with programmable inference arxiv.org. Checked 19 October 2026.
  2. Personal Statement on AI Risk docs.google.com. Checked 19 October 2026.
  3. Developing Bug-Free Machine Learning Systems With Formal Mathematics arxiv.org. Checked 19 October 2026.
  4. Machine Problem Solving math.washington.edu. Checked 19 October 2026.
  5. Learning a SAT Solver from Single-Bit Supervision arxiv.org. Checked 19 October 2026.
  6. GPT-4 Technical Report arxiv.org. Checked 19 October 2026.
  7. OpenAI o1 System Card arxiv.org. Checked 19 October 2026.
  8. Inside OpenAI’s quest to make AI do anything for you techcrunch.com. Checked 19 October 2026.
  9. Competitive Programming with Large Reasoning Models arxiv.org. Checked 19 October 2026.