Post-Doctorates

Bruno Brandoli Machado

Bruno Brandoli Machado

I obtained my B.S. degree in Computer Engineering in 2007 from Dom Bosco Catholic University, my M.Sc. and Ph.D. in Computer Science from University of São Paulo, in 2010 and 2016, respectively.

Areas of interest: 

  • Modelos de Aprendizagem Profunda
  • Visão Computacional
  • Predição de Eventos
  • Deep Learning
  • Computer Vision
  • Event Forecasting

Jamille Feitosa

Jamille Feitosa

Undergraduated in Physics from UESC (2012), Master in Physics with emphasis on Astrophysics from UESC (2015), and PHD in Physics Applied to Medicine with emphasis on Neuroscience at UNICAMP. Currently enrolled as a postdoctoral researcher at FGV.

Areas of interest: 

  • Machine learning
  • Processamento de imagens médicas
  • Neurociências

Oscar Alfredo Sierra Fonseca

Oscar Alfredo Sierra Fonseca

Graduated in Mathematics from Universidad Nacional de Colombia Bogotá D.C. (2013) , master in Mathematics from Universidade Federal do Rio de Janeiro (2016) and PhD in Mathematics at Universidade Federal do Rio de Janeiro(2021).

ÁREAS DE INTERESSE:

  • Teoria de controle e estabilização 
  • Controle Ótimo

Elias da Conceição Rodrigues

Elias da Conceição Rodrigues

Bacharel em Física pela Universidade do Estado do Rio de Janeiro (2008) e Mestrado em Engenharia Civil pela COPPE-UFRJ (2011) com ênfase em Geofísica Computacional, onde trabalhou com Propagação de Ondas Sísmicas e Modelagem Computacional. Doutorado em Engenharia Mecânica na PUC-Rio (2018), na área de Reologia de Materiais Complexos e Mecânica dos Fluidos Não-Newtoninaos, sob orientação do Professor Paulo Roberto de Souza Mendes, trabalhando no desenvolvimento de modelos constitutivos tixotrópicos.

Philip Ovington

Philip Ovington

Interests: Graph representation learning, Link prediction, Biological networks (especially drug-drug interaction networks), Recommender systems, Reducing bias in parameter estimation, Contrastive learning, MCMC Sampling and machine learning application in biology and health.

 

Rodrigo Barreto Alves

Rodrigo Barreto Alves

I have a degree in Actuarial Science from the Federal University of Rio de Janeiro (2013) and a Master's degree in Mathematics from the Pontifical Catholic University of Rio de Janeiro (2017). I did my Ph.D. in Statistics under the supervision of Glauco Valle and  Giulio Iacobelli at the Federal University of Rio de Janeiro (2022). I have experience teaching at the State University of Rio de Janeiro and the Federal Rural University of Rio de Janeiro. My research interests are in Probability, Stochastic Processes, and their applications.

Helton Graziadei de Carvalho

Helton Graziadei de Carvalho

Holds a bachelor's degree in Statistics (2013), a master's degree in Statistics (2015), and a doctor's degree in Statistics from the University of Sao Paulo. During his doctorate, he was a visiting scholar at Bocconi University (2018-2019). He was also a lecturer in Statistics at the Federal University of Santa Catarina (2021). Currently, he is a post-doc in Statistics at the School of Applied Mathematics from Fundacao Getulio Vargas (EMAp/FGV).

Areas of Interest:

  • Time Series
  • Bayesian Inference
  • Non-parametric Statistics

Eduardo Fraga Lima de Melo

Eduardo Fraga Lima de Melo

Undergraduate degree in Actuarial Science (merit Magna Cum Laude) from the Federal University of Rio de Janeiro (2001), a master's degree in Business Administration (Finance) from the COPPEAD Business School / UFRJ (2004) and a PhD in Business Administration (Finance research line) from the COPPEAD Business School / UFRJ (2008). Doctoral visiting scholar at Cass Business School, City University, London / United Kingdom.

Eliezer de Souza da Silva

Eliezer de Souza da Silva

My main research interest is designing efficient algorithms and principled methods for Machine Learning and Artificial Intelligence problems, ranging from proposing models, learning algorithms, inference, and prediction. I have an interest in variational inference and other scalable and approximate inference methods, as well as causal inference methods. I obtained my Ph.D.

Raphael Tinarrage

Raphael Tinarrage

I did the essential part of my mathematical education at the Institut de Mathématiques d'Orsay, in the south of Paris. I passed by the ENS Saclay, where I obtained my agrégation (teaching diploma). I then followed a research master in mathematics applied to life sciences.

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