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
- Fields
- Reinforcement learning, Robotics
- 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
- Began a PhD in electrical engineering and computer sciences at UC Berkeley, advised by Sergey Levine.2
- Began work as a student researcher and research intern at Google.2
- Started a research internship at DeepMind on multi-agent inverse reinforcement learning.2
- Posted D4RL, datasets for deep data-driven reinforcement learning, as first author.4
- Joined Waymo as a research scientist.2
- 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.
Where they work
- Waymo 4 people in the wiki
Related people
- Dmitri DolgovAlso at Waymo
- Tekedra MawakanaAlso at Waymo
- Satish JeyachandranAlso at Waymo
- Bob McGrewRobotics · Reinforcement learning
- Tuomas HaarnojaReinforcement learning · Robotics
- Sergey LevineRobotics · Reinforcement learning
- Misha DenilRobotics · Reinforcement learning
- Jonathan HurstRobotics · Reinforcement learning
- Deepak PathakRobotics · Reinforcement learning
- Vikash KumarRobotics · Reinforcement learning
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References
5 sources · profile reviewed Oct 22, 2026 · data updated Oct 22, 2026