Technical Experience
- Autonomous driving systems for production
- Computer vision, scene understanding and reinforcement learning research
- Robotics architecture design
- Technical leader delivering complex systems
Dr. David Paz specializes in autonomy holding a Ph.D. in Computer Science from the University of California San Diego (UCSD). His research has resulted in ADAS and robotic algorithms including road user trajectory prediction, AI planning, and dynamic scene understanding. His practical experience is highlighted by affiliations such as Bosch Research, where he contributed to developing AI models for mapless, predictive vehicle navigation and planning, successfully translating academic rigor into industrial applications.
2023-Present
Building and leading the development of next generation AI planning and scene understanding for parking and autonomous driving technology.
2017-2023
Developed road-user trajectory prediction, intent recognition, and dynamic scene understanding models to address the scalability constraints from current state of the art architectures.
2021
Quantified key performance benefits and constraints of flow data in an online perception system. Designed and implemented a context-aware tracking framework for occlusion scenarios.