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Alberto Sangiovanni-Vincentelli
Researcher at University of California, Berkeley
Publications - 946
Citations - 47259
Alberto Sangiovanni-Vincentelli is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Logic synthesis & Finite-state machine. The author has an hindex of 99, co-authored 934 publications receiving 45201 citations. Previous affiliations of Alberto Sangiovanni-Vincentelli include National University of Singapore & Lawrence Berkeley National Laboratory.
Papers
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Journal ArticleDOI
System Level Design for Clustered Wireless Sensor Networks
TL;DR: This work presents a system level design methodology for clustered wireless sensor networks based on a semi-random communication protocol called SERAN, a mathematical model that allows to optimize the protocol parameters, and a network initialization and maintenance procedure.
Journal ArticleDOI
Limitations and challenges of computer-aided design technology for CMOS VLSI
R.E. Bryant,Kwang-Ting Cheng,Andrew B. Kahng,Kurt Keutzer,W. Maly,Richard Newton,Larry Pileggi,Jan M. Rabaey,Alberto Sangiovanni-Vincentelli +8 more
TL;DR: Limits to how design technology can enable the implementation of single-chip microelectronic systems that take full advantage of manufacturing technology with respect to such criteria as layout density performance, and power dissipation are explored.
Proceedings ArticleDOI
Fault-tolerant deployment of embedded software for cost-sensitive real-time feedback-control applications
TL;DR: This work proposes a synthesis-based design methodology that relieves the designers from the burden of specifying detailed mechanisms for addressing platform faults, while involving them in the definition of the overall fault-tolerance strategy.
Proceedings ArticleDOI
Cut-off in engine control: a hybrid system approach
TL;DR: A novel approach to the control of an automotive engine in the cut-off region is presented, which is formulated as a hybrid optimization problem, whose solution is obtained by relaxing it to the continuous domain and mapping its solution back into the hybrid domain.
Proceedings Article
Data-Driven Probabilistic Modeling and Verification of Human Driver Behavior
Dorsa Sadigh,Katherine Driggs-Campbell,Alberto Puggelli,Wenchao Li,Victor Shia,Ruzena Bajcsy,Alberto Sangiovanni-Vincentelli,S. Shankar Sastry,Sanjit A. Seshia +8 more
TL;DR: A novel stochastic model of the driver behavior based on Markov chains in which the transition probabilities are only known to lie in convex uncertainty sets is proposed, and properties of the model expressed in probabilistic computation tree logic (PCTL) are formally verified.