Education

• BSc. in Statistics - Universidade Federal de Minas Gerais, Brazil. 2004

• MSc. in Statistics - Universidade Federal do Rio de Janeiro, Brazil. 2006

• PhD. in Statistics - University of Warwick, UK. 2011

• Inference for stochastic processes

• Stochastic simulation

• Computational Statistics and Monte Carlo methods

• Geostatistics

• Bayesian Statistics

• Mathematical Statistics

• Item response theory

Selected publications

• Exact Bayesian inference for diffusion driven Cox processes. To appear in Journal of the American Statistical Association, 2023. (with K. G. Latuszynski and G. O. Roberts). 

• Exact Monte Carlo likelihood-based inference for jump-diffusion processes. Journal of the Royal Statistical Society - Series B, v. 85, p. 732-756, 2023. (with K. G. Latuszynski and G. O. Roberts).

• Exact Bayesian inference for level-set Cox processes with piecewise constant intensity function|. Journal of Computational and Graphical Statistics, v. 32, p. 1-18, 2023. (with B. C. C. Dias)

• Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes. Statistics and Computing, v. 32, 14, 2022. (with L. M. Dutra and R. W. C. Silva)

• Efficient Bernoulli factory MCMC for intractable posteriors. Biometrika, v. 109, p 369-385, 2022. (with D. Vats, K. G. Latuszynski and G. O. Roberts). 

• Corrigendum: Exact Bayesian inference in spatio-temporal Cox processes driven by multivariate Gaussian processes. Journal of the Royal Statistical Society - Series B,  v. 85, p. 176, 2023. (with D. Gamerman) 

• Exact Bayesian inference in spatio-temporal Cox processes driven by multivariate Gaussian processes. Journal of the Royal Statistical Society - Series B,  v. 80, p. 157-175, 2018. (with D. Gamerman) 

• A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions. Journal of the Royal Statistical Society - Series C, v. 66, p. 387-412, 2017. (with V. D. Mayrink). 

• Exact simulation problems for jump-diffusions. Methodology and Computing in Applied Probability, v. 16, p. 907-930, 2014. (with G. O. Roberts). 

Other journal papers and preprints

• Multidimensional Bayesian IRT Model for Hierarchical Latent Structures. [arXiv:2006.09966] (with J. Venturelli and D. F. Andrade).

• Flexible Bayesian modelling in dichotomous item response theory using mixtures of skewed item curves. British Journal of Mathematical and Statistical Psychology, v. 76, p. 69-86, 2022. (with J. Venturelli and R. Loschi).

• On the definition of likelihood function. [arXiv:1906.10733] (with P. Franklin).

•  Bayesian linear regression models with flexible error distributions. Journal of Statistical Computation and Simulation, v. 90, p. 2571-2591, 2020.  (with N. B. da Silva and M. Prates). 

• Identifying down and up-regulated chromosome regions using RNA-Seq data. Statistical Methods and Applications, v. 29, p. 619-649, 2020. (with V. D. Mayrink).

• Robust Bayesian model selection for heavy-tailed linear regression using finite mixtures. Brazilian Journal of Probability and Statistics, v. 34, p. 51-70, 2020. (with M. Prates and V. H. Lachos). 

• Bayesian modelling of the abilities in dichotomous IRT models via regression with missing values in the covariates. Brazilian Journal of Probability and Statistics, v. 33, p. 782-800, 2019. (with B. C. C. Dias). 

• Bayesian Item Response model: a generalised approach for the abilities' distribution using mixtures. Journal of Statistical Computation and Simulation. v. 88, p. 967-981, 2018. (with B. C. C. Dias and T. M. Soares). 

• Barker's algorithm for Bayesian inference with intractable likelihoods. Brazilian Journal of Probability and Statistics, v. 31, p. 732-745, 2017.  (with K. G. Łatuszyński and G. O. Roberts). 

• Simultaneous Multifactor DIF Analysis and Detection in Item Response Theory. Computational Statistics & Data Analysis, v. 59, p. 144-160, 2013. (with D. Gamerman and T. M. Soares). 

• An integrated Bayesian model for DIF analysis. Journal of Educational and Behavioral Statistics, v. 34, p. 348-377, 2009. (with D. Gamerman and T. M. Soares). 

• Análise Bayesiana do Funcionamento Diferencial do Item. Pesquisa Operacional, v. 27, p. 271-291, 2007. (with D. Gamerman and T. M. Soares). 

• Avaliação de uma medida de evidência de um ponto de mudança e sua utilização na identificação de mudanças na taxa de criminalidade em Belo Horizonte. Pesquisa Operacional, v. 25, n. 3, p. 449-463, 2005. (with R. H. Loschi and F. R. B. Cruz).

Books

• Stochastic Simulation and Statistical Inference for Diffusion Processes. 1 ed.: Associação Brasileira de Estatística, 2012. (in Portuguese)

Book chapters

• Differential Item Functioning. In: Wim J. van der Linden (Eds.). Handbook of Item Response Theory - Volume Three. 1 ed.: Chapman and Hall/CRC, 2018. (with D. Gamerman and T. M. Soares)
• Bayesian analysis in Item Response Theory applied to a large-scale educational assessment. In: Mike West; Tony O'Hagan. (Eds.). The Oxford Handbook of Applied Bayesian Analysis. 1 ed.: Oxford University Press, 2010. (with D. Gamerman and T. M. Soares)

PhD students

• Gracielle Antunes (UFMG, 2022- )
• Izabel N. de Souza (UFRJ, jointly with Dani Gamerman, 2022- )
• Larissa N. A. Martins (UFMG, jointly with Thais Paiva, 2020-2024)
• Guilherme A. S. Aguilar (UFMG, 2017-2022)
• Bárbara C. C. Dias (UFMG, 2015-2019)
• Juliane V. S. Lima (UFMG, 2015-2019)
• Lívia  M. Dutra (UFMG, jointly with Roger W. C. Silva, 2015-2019)
• Pedro F. C. Silva (UFMG, 2015-2017)
• Nívea B. da Silva (UFMG, jointly with Marcos O. Prates, 2014-2017)