Quan Vuong

Co-Founder at Physical Intelligence

RoboticsTransformer models (RT-X)Physical AIMachine Learning researchFull-stack architectureResearch leadership
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About

I'm Quan Vuong, Co-Founder at Physical Intelligence. My work sits at the intersection of large-scale machine learning and physical robotics, a journey that has taken me from building full-stack car telemetry systems to co-leading the RT-X and Open X-Embodiment initiatives at Google DeepMind. With a PhD in Computer Science from UC San Diego, I am deeply passionate about 'ImageNet-like' scaling for robot actions and fostering open, collaborative research. Currently, I am focused on scaling Physical Intelligence and am actively looking for exceptional researchers and engineers to join us in solving some of the most challenging problems in physical AI. Whether you're interested in cross-robot learning or looking for a high-impact technical role, I'm always keen to connect with top-tier talent and the broader research community.

Networking

What I can offer

  • ›Deep expertise in robotics and Transformer models
  • ›Insights into scaling physical AI
  • ›Mentorship for research interns and engineers
  • ›Experience in full-stack architecture and technical consulting

Looking for

  • ›Exceptional researchers and engineers (research and full-stack)
  • ›Referrals for top-tier technical talent
  • ›Collaboration with the high-level robotics research community

Best fit for

Robotics researchersFull-stack engineersAI academicsTechnical talent looking for startup opportunities

Current Interests

Physical AICross-robot learningScaling laws in roboticsMentorship and hosting research interns

Background

Career

Transitioned from software engineering and technical consulting into deep academic research in robotics, culminating in a PhD and a research leadership role at Google DeepMind before co-founding Physical Intelligence.

Education

PhD in Computer Science, UC San Diego (2018–2022); Bachelor’s Degree in Mathematics, NYU Abu Dhabi (2013–2017).

Achievements

  • ›Won ICRA 2024 Best Paper Award and Best Manipulation Paper Award
  • ›Co-led RT-X and Open X-Embodiment (OXE) initiatives at Google DeepMind
  • ›Published research featured as ECCV 2024 Oral and ICLR 2024 Spotlight
  • ›Built a food distribution network reaching $1,600 USD weekly revenue in six weeks

Opinions

  • TypeScript is superior to JavaScript for large-scale projects
  • Robotics requires 'ImageNet-like' scaling for robot actions and cross-robot learning
  • Open-source collaboration is essential for robotics progress (e.g., Open X-Embodiment dataset)