Xu Han
Postdoctoral Researcher at University of California, Los Angeles
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolXu Han is a postdoctoral researcher at the UCLA Mobility Lab specializing in perception, planning, and control for automated driving systems, with five years of hands-on experience bridging digital twin simulation and real-world vehicle deployments. He holds a PhD from UCLA and a strong ML/deep learning background, complemented by proficiency in simulators like CARLA, LGSVL, and Vissim. Xu has contributed to the open-source OpenCDA project—implementing core platooning controllers and map corrections—demonstrating practical expertise in cooperative driving frameworks. His work uniquely blends multi-agent reinforcement learning research with production-oriented testing on actual ADS platforms, making him adept at moving algorithms from simulation to road-ready validation. Based in Los Angeles, he brings a rare combination of simulation scripting, systems integration, and field validation to mobility research.
5 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BS), Electrical and Electronics Engineering, Bachelor of Science (BS), Electrical and Electronics Engineering at University of CincinnatiMaster of Science - MS, Electrical and Electronics Engineering, Master of Science - MS, Electrical and Electronics Engineering at Washington University in St. LouisDoctor of Philosophy - PhD, Civil Engineering, Doctor of Philosophy - PhD, Civil Engineering at University of California, Los Angeles
English, Chinese
Github Skills (6)
python10
autonomous-driving9
c-language8
simulation8
simulations8
cprogramming-language8
Programming languages (3)
Github contributions (5)
ucla-mobility/OpenCDA
Feb 2021 - Nov 2022
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 53 commits, 6 PRs in 1 year 9 months
Contributions summary:Xu primarily contributed to the core functionalities within the `opencda` repository, with a focus on the GFS (Generalized Framework for full-stack cooperative driving automation) controller. The user implemented and refined the GFS controller class, which calculates platoon index and speed. Changes included updates to vehicle classes, and integration with core platooning modules, and the correction of y-coordinate mappings for the customized map.
cooperative-driving-automationfull-stackprototypingsimulationautomated-driving-systems
xuhan417/OpenCDA
Feb 2022 - Mar 2025
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.
Contributions:1 PR, 48 pushes, 12 branches in 3 years 1 month
fairness-mlcooperative-driving-automationmultiagent-reinforcement-learningfull-stackprototyping
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