CV Lattes
Universidade de São Paulo (USP). Instituto de Física (IF) (Institutional affiliation from the last research proposal) Birthplace: Brazil
is specialized in R&D, focusing on machine learning, privacy and healthcare. After finishing his PhD in statistical physics at the University of São Paulo in 2015, did postdoctoral research on machine learning at three top French institutions (ENS/CEA/Inria), between 2015 and 2018. Between 2018 and 2021, has worked with machine learning and privacy at Owkin, a French startup, and with medical data at the Albert Einstein Hospital in Brazil. Since July 2021, is a research engineer at Microsoft. In his academic and profissional career, has co-authored 18 publications, from which 11 have appeared in conferences (including machine learning conferences such as ICML, NeurIPS and ICLR), 3 in journals, 1 as a book chapter, and 3 as preprints. (Source: Lattes Curriculum)
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We propose to study, within a statistical mechanics point of view, aspects of problems in information security, in particular those of estimate of reputations and steganography. Using recently established connections between statistical mechanics and processes of inference and optimization, we are able to analyze algorithms used in the study of such problems, determining bounds in its per…
Bayesian inference models are specially useful in the description of processes in which, from noise-corrupted measurements, one wishes to estimate the systems current state. In the last decades, tools from the statistical mechanics of disordered systems have been used in the study of such models; in particular, in the last few years, it has been noted a great similarity between the cavity…
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