Songan Zhang is a tenure-track associate professor and robotics researcher with eight years of experience bridging academic research and industry R&D in autonomous vehicles. Trained at Tsinghua (BS/MS) and the University of Michigan (PhD, Mechanical Engineering), he specializes in reinforcement learning and meta-reinforcement learning for control policy design, as well as LiDAR–camera fusion for AV perception. He has translated doctoral and postdoc work into applied research roles at Ford and now leads academic projects at Shanghai Jiao Tong University, bringing production-oriented rigor to scholarly work. Songan’s background blends deep theoretical training in stochastic processes and machine learning with hands-on systems experience in object detection, tracking, and vehicle control. Colleagues note his uncommon combination of automotive engineering roots and modern ML expertise, enabling rapid prototyping from sensor fusion to control. Based in California and active across US–China research networks, he focuses on turning cutting-edge learning algorithms into robust, deployable AV technologies.
8 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Mechanical Engineering, Doctor of Philosophy - PhD, Mechanical Engineering at University of Michigan
Master's degree, Automotive Engineering Technology/Technician, Master's degree, Automotive Engineering Technology/Technician at Tsinghua University
Contributions:136 pushes, 4 branches in 3 years 1 month
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