Jonathan Lee
Senior Manager at FlowMo Technologies, Inc.
Fremont, California, United States
Summary
👤
Senior🎓
Top SchoolJonathan Lee is a senior manager and entrepreneur based in Fremont with 12 years of experience bridging academic research, data science, and transportation systems engineering. At UC Berkeley’s Mobile Sensing Lab he leads applied research in connected and autonomous vehicle technologies and was chief engineer and co-PI of the CIRCLES Consortium, translating multidisciplinary science into deployable traffic solutions. Formerly a Sr. Data Scientist at Uber, he brings production-scale analytics and simulation expertise—contributing backend refactors and traffic RL tooling to the open-source flow project—to problems in routing, traffic simulation, and vehicular logistics. Trained as a computational research scientist with a PhD in Mechanical Engineering and postdoctoral work at Sandia, his background spans molecular dynamics, fluids DFT, and machine learning, enabling rigorous, physics-informed modeling approaches. As CEO and co-founder of FlowMo Technologies, he combines research rigor with product-building instincts to commercialize traffic and mobility innovations. Notably, his work often blends atomistic-to-continuum thinking with large-scale systems design, allowing uncommon cross-pollination between materials simulation and real-world transportation problems.
12 years of coding experience
11 years of employment as a software developer
B.S., Engineering Physics, B.S., Engineering Physics at University of California, BerkeleyPh.D., Mechanical Engineering, Ph.D., Mechanical Engineering at Rice University
English, Chinese
Github Skills (6)
python10
reinforcement-learning10
testing10
pandas9
automated-tests8
git7
Programming languages (6)
Github contributions (5)
flow-project/flow
May 2020 - Sep 2020
Computational framework for reinforcement learning in traffic control
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:427 commits, 36 PRs, 257 pushes in 3 months
Contributions summary:Jonathan primarily focused on refactoring and improving the base classes within the project, converting them into abstract base classes. They implemented dummy methods and fixed various import statements and assertion checks, likely to facilitate testing. The user also made changes to the time-space diagram plotting, utilizing pandas for data reshaping and generalizing the plotting for all networks. Furthermore, they contributed to the implementation of highway networks for time-space diagrams, and also updated the base controller with failsafes.
autonomousreinforcement-learningvehicle-controldeep-reinforcement-learningbenchmark
CIRCLES-consortium/CIRCLES-consortium.github.io
Jun 2020 - Sep 2023
Contributions:2 reviews, 90 pushes, 1 branch in 3 years 3 months
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