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, with a particular focus on the intersection between machine learning 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 2020, was a machine learning scientist at a French startup, focusing in privacy issues emerging in the interaction between hospitals and pharmaceutical companies. Since March 2020, is a data scientist at Hospital Israelita Albert Einstein. In his academic and profissional career, has co-authored 12 publications, from which 8 have appeared in conferences (including machine learning conferences such as ICML and NeurIPS), 2 in journals, 1 as a book chapter, and 1 as preprint. (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…
| 1 / 1 | Completed scholarships in Brazil |
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