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Rodrigo de Salvo Braz
Senior Computer Scientist, Artificial Intelligence Center
Rodrigo de Salvo Braz, Ph.D., focuses on probabilistic inference and learning, particularly the application of symbolic manipulation to probabilistic programs. This includes lifted first-order probabilistic inference, the subject of his Ph.D. thesis at the University of Illinois at Urbana-Champaign in collaboration with Eyal Amir, Ph.D., under supervision of Dan Roth, Ph.D.
He has worked on several DARPA projects, serving as PI of the SRI team in the Probabilistic Programming for Advanced Machine Learning (PPAML) program. He also was a team member on projects in machine reading, bootstrapped learning, and CALO (while at Berkeley).
Prior to SRI, de Salvo Braz was a postdoctoral researcher at the University of California, Berkeley, for Stuart Russell, Ph.D., where he worked on the BLOG (Bayesian Logic) probabilistic programming language.
He spent two years as a graduate student at the Cognitive and Linguistic Sciences Department at Brown University. He holds a B.S. and M.S. in computer science from the University of São Paulo, Brazil.