Summary
David Paz is a research scientist specializing in autonomy with nine years of experience building perception, prediction, and learning systems for self-driving vehicles and robotics. Holding a Ph.D. in Computer Science from UC San Diego, he led the Autonomous Vehicle Laboratory where he advanced trajectory prediction, intent recognition, and scalable scene-understanding architectures while also contributing to mapping, localization, planning and control for on-campus delivery vehicles. Currently at Bosch, he applies perception and machine learning research to commercial autonomy applications, and previously shipped occlusion-aware tracking features on full-scale autonomous trucks at TuSimple. His background spans embedded acceleration, HPC containerization, and portable sensing, reflecting a blend of low-level systems thinking and high-level probabilistic modeling. Based in San Diego, he’s a hands-on roboticist who bridges academic rigor with production constraints to make AV systems more robust and scalable.
9 years of coding experience
2 years of employment as a software developer
University of California, San Diego
Electrical and Computer Engineering, Computer Engineering, Electrical and Computer Engineering, Computer Engineering at University of California, San Diego - Jacobs School of Engineering