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Justin Fu

Research scientist, Waymo Research (since August 2021), Waymo

  • Research scientist, Waymo Research (since August 2021), Waymo12

Justin Fu is a machine learning researcher at Waymo Research. Fu's CV describes the role of lead developer for Waymax, an open-source, hardware-accelerated simulator for planning and behavior research in autonomous driving, and Fu is one of four equal-contribution first authors of the Waymax paper. Before Waymo, Fu completed a PhD at UC Berkeley advised by Sergey Levine, with research on reinforcement learning including the D4RL benchmark.1234

At a glance

Current role
Research scientist, Waymo Research (since August 2021)
Company
Waymo
Sector
Company
Education
UC Berkeley
Work listed
2
Sources cited
5
Profile reviewed

Career

Fu completed a PhD in electrical engineering and computer sciences at UC Berkeley from 2016 to 2021, advised by Sergey Levine. During the PhD, Fu was a student researcher at Google and a research intern at DeepMind, working on inverse reinforcement learning.12

Fu joined Waymo as a research scientist in August 2021. Fu's CV lists work on reinforcement-learning fine-tuning of driving foundation models and on combining such models with search and optimization for reliability.2

Research

Fu's research covers reinforcement learning, natural language processing and robotics. Fu was first author of D4RL (2020), datasets for deep data-driven reinforcement learning, and co-organized the NeurIPS 2021 Workshop on Offline Reinforcement Learning.124

At Waymo, Fu was lead developer of Waymax, released in 2023 as an open-source simulator for planning and behavior problems in autonomous driving. The Waymax paper lists Cole Gulino, Fu, Wenjie Luo and George Tucker as equal-contribution first authors.235

Work and contributions

  • Waymax Open-source code

    Lead developer of Waymax and an equal-contribution first author of its 2023 paper, which presents an accelerated, data-driven simulator for large-scale autonomous driving research.235

  • D4RL Open data

    First author of D4RL (2020), a set of datasets and benchmarks for offline, data-driven reinforcement learning.4

Timeline

  1. Began a PhD in electrical engineering and computer sciences at UC Berkeley, advised by Sergey Levine.2
  2. Began work as a student researcher and research intern at Google.2
  3. Started a research internship at DeepMind on multi-agent inverse reinforcement learning.2
  4. Posted D4RL, datasets for deep data-driven reinforcement learning, as first author.4
  5. Joined Waymo as a research scientist.2
  6. Posted the Waymax simulator paper as an equal-contribution first author.32

Other documented roles

Roles the sources document that are not confirmed as current.

  • Research intern (2019–2020), DeepMind2
  • Student researcher and research intern (2018–2019), Google2

Where they work

  • Waymo 4 people in the wiki

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References

5 sources · profile reviewed Oct 22, 2026 · data updated Oct 22, 2026

  1. Justin Fu — personal siteJustin Fu · Official page · accessed Oct 22, 2026
  2. Justin Fu — CVJustin Fu · Official page · accessed Oct 22, 2026
  3. Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research (arXiv 2310.08710)arXiv · Paper · published Oct 12, 2023 · accessed Oct 22, 2026
  4. D4RL: Datasets for Deep Data-Driven Reinforcement Learning (arXiv 2004.07219)arXiv · Paper · published Apr 15, 2020 · accessed Oct 22, 2026
  5. waymo-research/waymax READMEWaymo Research (GitHub repository) · Repository · accessed Oct 22, 2026