Alberto Sangiovanni‐Vincentelli
University of California, Berkeley, Technical University of Munich
Papers
11
Total Citations
300
H-Index
7
About
Alberto Sangiovanni-Vincentelli is a pioneer in the design and verification of cyber-physical systems (CPS), with a career spanning foundational contributions to electronic design automation (EDA) and formal methods. His recent work focuses on the intersection of machine learning, control, and formal logic, particularly through the development of Scenic, a probabilistic programming language for scenario specification and data generation in CPS (83 citations). He also introduced Satisfiability Modulo Convex Programming (SMC), a powerful framework that bridges discrete Boolean reasoning with continuous convex constraints, enabling efficient verification and control of hybrid systems (49 citations). His motion planning algorithms, such as the scalable lazy SMT-based approach (32 citations) and LTL-based multi-robot planning (48 citations), have advanced the field of autonomous robotics by providing provably correct, computationally tractable solutions. With over 100,000 citations and numerous awards, including the IEEE Robert N. Noyce Medal and the ACM/IEEE A. Richard Newton Technical Impact Award, Sangiovanni-Vincentelli’s work continues to shape the future of safe, intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Scenic: a language for scenario specification and data generation83 citations · 2022
- 2SMC: Satisfiability Modulo Convex Programming49 citations · 2018
- 3
- 4SMC42 citations · 2017
- 5Scalable lazy SMT-based motion planning32 citations · 2016
- 6ACTUAL ENGAGED GEAR IDENTIFICATION: A HYBRID OBSERVER APPROACH16 citations · 2005
- 7Scenic: A Language for Scenario Specification and Data Generation14 citations · 2020
- 8
- 9Contract-Based Specification Refinement and Repair for Mission Planning5 citations · 2023
- 10Symbiotic CPS Design-Space Exploration through Iterated Optimization3 citations · 2023