---
title: Will Brown
category: people
role: Researcher
company: Prime Intellect
linkedin: "https://www.linkedin.com/in/willcb/"
twitter: "https://x.com/willccbb"
website: "https://willcb.com"
sourceLabels:
  - Official speaker roster
  - Official conference schedule
last_auto_summarized: '2026-07-03T05:05:08.328Z'
---
# Will Brown

## Profile
Researcher at [[prime-intellect|Prime Intellect]].

- [LinkedIn](https://www.linkedin.com/in/willcb/)
- [X / Twitter](https://x.com/willccbb)
- [Website](https://willcb.com)

## Biography
Will Brown leads Applied Research at [[prime-intellect|Prime Intellect]], where his work centers on open research infrastructure for training, deploying, and self-improving frontier agentic models. At AI Engineer World's Fair 2026, he is presenting both a workshop on the [[prime-intellect|Prime Intellect]] stack and a session on reinforcement learning without verifiable rewards, connecting [[prime-intellect|Prime Intellect]]'s broader open AI infrastructure agenda with concrete posttraining and midtraining research problems. He holds a PhD in Computer Science from Columbia University.

## Conference Sessions
- [[2026-06-29-will-brown-the-prime-intellect-stack]] — The Prime Intellect Stack (2026-06-29, 4:30pm-5:30pm)
- [[2026-06-30-will-brown-reinforcement-learning-without-verifiable-rewards]] — Reinforcement Learning without Verifiable Rewards (2026-06-30, 1:30pm-1:50pm)

## Evidence Graph
This evidence graph summarizes how this person appears across the conference source graph: scheduled sessions, linked videos, transcripts, and slide-derived evidence.

### Linked Sessions
- [[2026-06-29-will-brown-the-prime-intellect-stack|The Prime Intellect Stack]]
- [[2026-06-30-will-brown-reinforcement-learning-without-verifiable-rewards|Reinforcement Learning without Verifiable Rewards]]

### Media Signals
- `youtube-PbHm2qKnu10` — 6 slide-derived text signals
- Slide-derived themes for `youtube-PbHm2qKnu10`: kinda, works, labs, doing, four, steps, matches, performance.
- Evidence links for `youtube-PbHm2qKnu10`: [[youtube-PbHm2qKnu10]], [[youtube-PbHm2qKnu10-slides]], [[youtube-PbHm2qKnu10-dense-slides]], [[youtube-PbHm2qKnu10-reconstructed-slides]]
- `youtube-JIsgyk0Paic` — 8 slide-derived text signals
- Slide-derived themes for `youtube-JIsgyk0Paic`: many, pipelines, feedback, best, practices, level, systems, take.
- Evidence links for `youtube-JIsgyk0Paic`: [[youtube-JIsgyk0Paic]], [[youtube-JIsgyk0Paic-slides]], [[youtube-JIsgyk0Paic-dense-slides]], [[youtube-JIsgyk0Paic-reconstructed-slides]]