Dr. Antonio J. Salazar
Dr. Antonio J. Salazar is a senior engineer in the DesignWare IP Prototyping team at Synopsys, where he is the lead engineer for strategic and methodology development. Prior to joining Synopsys, he was an Associate Professor at Universidad Simon Bolivar, where he was responsible for multiple financed projects, including inter-departmental industry-university projects management and technical and engineering degree student supervision, as well as being the founder and coordinator of the Center of Assistive Technology (CETA) and coordinator of the Center of Design of Integrated Circuits (CDCI).
Dr. Salazar received a Doctoral Grant from Portugal’s Science and Technology Foundation (FCT), that gave him the opportunity to join the Institute for Systems and Computer Engineering of Porto (INESC-Porto), as a Researcher of the Optoelectronics and Electronics Systems Unit (UOSE) and a Collaborator for Telecommunications and Multimedia Unit (UTM), focusing on assistive technology, augmented living and design for testability; which included collaborating with projects such as the Prolimb, Human Re-Learning and BioSWIM of INESC-Porto, as well as international efforts such as Towards One European Test Solution (TOETS) and European library-based flow of embedded silicon test Instruments (ELESIS), authoring a number of peer-reviewed publications.
Dr. Salazar obtained a B.Sc. in electrical engineering from Caltech, where he joined the Pine Lab’s Neuro-Probe project, an in vivo attempt to create a bi-directional link with living neurons. After that he pursued an M.Sc. in electrical and computer engineering, majoring in integrated circuits, from U.C. Santa Barbara. His master’s thesis was entitled “On Forced Variable Reintroduction for BDD Simplification.” Later he obtained a Ph.D. with honors from the Universidade do Porto, with a thesis entitled “Mixed-signal Test and Measurement Framework for Wearable Monitoring System,” a framework for mixed-signal sensor-based systems’ testability, maintenance, and reliability, based on in-situ access mechanism applying element grouping strategies.