David Paz

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Biography

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.

AI Techlead and Senior Scientist @ Bosch Center for AI

Sunnyvale, CA

Technical Experience & Education

Technical Experience

  • Autonomous driving systems for production
  • Computer vision, scene understanding and reinforcement learning research
  • Robotics architecture design
  • Technical leader delivering complex systems

Education Institutions

  • Computer Science and Engineering, PhD, UC San Diego.
  • Intelligent Systems, Robotics, and Control, M.S, UC San Diego.
  • Computer Engineering, B.S, UC San Diego.

Work Experience Timeline

2023-Present

Senior Research Scientist and Tech Lead, Bosch Center for AI

Building and leading the development of next generation AI planning and scene understanding for parking and autonomous driving technology.

2017-2023

Research Project Lead, AVL @ UC San Diego

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

Perception Engineer, TuSimple

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.

Selected Publications

  1. D. Paz, et al. (2020). Probabilistic semantic mapping for urban autonomous driving applications. IEEE/RSJ International Conference on Intelligent Robots and Systems
  2. H. Christensen, D. Paz, et al. (2021). Autonomous vehicles for micro-mobility. Autonomous Intelligent Systems
  3. H. Zhang, D. Paz, et al. (2023). Enhancing online road network perception and reasoning with standard definition maps. IEEE/RSJ International Conference on Intelligent Robots and Systems