Summary
Dan Jia is a Senior Deep Learning Engineer and PhD based in Munich with nine years of experience building perception systems for robotics and automotive applications. He has transitioned research breakthroughs into production-ready models—developing award-winning LiDAR/person detectors and high-frame-rate 2D LiDAR systems while leading deployment with PyTorch and ROS on embedded GPUs. At RWTH Aachen he won the JRDB 3D detection challenge and authored widely used repositories for 2D and 3D perception, later applying that expertise at Magna Electronics on radar and LiDAR perception for automotive products. Now at Qualcomm, he focuses on scaling advanced deep-learning solutions for real-world embedded platforms. Trained in aerospace and mechanical engineering (BS, MS) before earning a PhD in computer science, he brings a rare blend of control, perception, and systems engineering. Colleagues rely on him for mentoring and for turning research code into robust, real-time systems that run on constrained hardware.
9 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at RWTH Aachen University
Master of Science - MS Mechanical Engineering, Master of Science - MS Mechanical Engineering at ETH Zürich
Bachelor of Science - BS Aerospace Aeronautical and Astronautical Engineering, Bachelor of Science - BS Aerospace Aeronautical and Astronautical Engineering at University of Illinois Urbana-Champaign
English, Chinese, German