Thaís Paiva Galletti

Thaís Paiva Galletti

Assistant Professor - Department of Statistics

Federal University of Minas Gerais (UFMG)

Bio

Professor at the Department of Statistics at the Federal University of Minas Gerais (UFMG) since 2016. She has a degree in Actuarial Science from UFMG, a Master’s in Statistics also from UFMG, and a PhD in Statistics from Duke University, USA.

Some of her research projects include imputation methods for synthetic data, simulation of synthetic geographic coordinates for confidential databases, and imputation of multivariate continuous variables for non-random missing data.

Interests
  • Bayesian Statistics
  • Imputation Methods for Missing and Synthetic Data
  • Data Confidentiality
  • Spatial Statistics
Education

  • PhD in Statistical Science, 2014

    Duke University

  • Master's degree in Statistics, 2010

    Federal University of Minas Gerais (UFMG)

  • Bachelor's degree in Actuarial Science, 2008

    Federal University of Minas Gerais (UFMG)

Teaching

UFMG

2024/2:

2023:

  • EST047 - Actuarial Mathematics I

  • EST049 - Actuarial Mathematics II

  • EST053 - Computational Methods for Risk Analysis

  • EST053 - Actuary Topics: IBA Exam Preparation  

  • EST179 - Intro to Biostatistics

2022:

  • EST047 - Actuarial Mathematics I

  • EST049 - Actuarial Mathematics II

  • EST053 - Computational Methods for Risk Analysis

  • EST053 - Actuary Topics: IBA Exam Preparation  

  • EST057 - Intro to Statistics

  • EST179 - Intro to Biostatistics

Publications

Gamerman, Dani, Marcos O Prates, Thais Paiva, & Vinicius D Mayrink. 2021. Building a Platform for Data-Driven Pandemic Prediction: From Data Modelling to Visualisation – the CovidLP Project. CRC Press. https://www.routledge.com/9780367709976.
Paiva, Thais, & Jerome P. Reiter. 2017. “Stop or Continue Data Collection: A Nonignorable Missing Data Approach for Continuous Variables.” Journal of Official Statistics 33 (3): 579–99. https://doi.org/10.1515/jos-2017-0028.
Paiva, Thais, Avishek Chakraborty, Jerry Reiter, & Alan Gelfand. 2014. “Imputation of Confidential Data Sets with Spatial Locations Using Disease Mapping Models.” Statistics in Medicine 33 (11): 1928–45. https://doi.org/10.1002/sim.6078.

Contact

  • thaispaiva@est.ufmg.br
  • Av. Pres. Antônio Carlos, 6627, Belo Horizonte, MG 31270-901
  • Room 4059 - Institute of Exact Sciences