Markov Chain Monte Carlo, 3rd Edition

Dani Gamerman

• Ph.D. in Statistics, University of Warwick (1987)
• Professor Emeritus of Statistics, UFRJ (since 2021), previously Professor of Statistics from 1996 to 2019.
• Supervises graduate students and post-doctoral researchers.
• Author of Statistical Inference: an Integrated Approach and Building a Platform for Data-Driven Pandemic Prediction: From Data Modelling to Visualisation - The CovidLP Project (Chapman & Hall). Also author of books and monographs in Portuguese.
• Published in journals including Journal of the Royal Statistical Society (Series B & C), Biometrika, Bayesian Analysis, Annals of Applied Statistics, Statistics & Computing, and Science.
• Foundational and Opening Lecturer at the World Meeting of the International Society for Bayesian Analysis (ISBA) in 2024 and 2004. Invited lecturer at BISP, International Meeting of the Psychometric Society, International Valencia Meeting on Bayesian Statistics, and International Workshop on Statistical Modeling, among others.
• Visiting lecturer at UFMG, Carlos III-Madrid, Connecticut, University College London, and Duke. Colaborador honorífico of Universidade Rey Juan Carlos in Madrid.
• Invited seminars at numerous universities in Brazil and abroad.
• Associate Editor of Statistical Modeling, International Statistical Review, and Environmetrics. Former member of the Boards of Directors of ISBA and ABE (Brazilian Statistical Association). Elected member of ISI.
• Organizer of many scientific meetings in Brazil.
• Current research interests: dynamic models, extreme value theory, item response theory, spatial statistics, survival analysis, and Bayesian computation.

Hedibert Freitas Lopes

• Full Professor, Insper Institute of Education and Research (since 2013), leading the Data and Decision Sciences Unit.
• Previously held a decade-long tenure at the University of Chicago Booth School of Business.
• Charles Wexler Professor in Statistics, Arizona State University (2021-2023).
• Previously held positions at Fluminense Federal University and the Federal University of Rio de Janeiro.
• Ph.D., Institute of Statistics and Decision Sciences, Duke University.
• Author of approximately one hundred publications in selective journals, with over ten thousand citations on Google Scholar.
• Successfully supervised more than 40 graduate students, with several ongoing.
• ISI Fellow (2020). First Brazilian ISBA Fellow (2024).
• Delivered over two hundred invited talks and more than thirty short courses globally.
• Leads major research initiatives focused on time series and high-dimensional data.
• Peer reviewer for over 100 international journals.
• Associate Editor for Journal of Computational and Graphical Statistics. Served as AE for Bayesian Analysis, Journal of Business and Economic Statistics, and the Brazilian Journal of Probability and Statistics.

Flávio Bambirra Gonçalves

• Ph.D. in Statistics, University of Warwick (2011).
• Associate Professor of Statistics, Federal University of Minas Gerais (UFMG), Brazil.
• Research interests: Bayesian statistics, stochastic processes, stochastic simulation, computational statistics, geostatistics, item response theory, and mathematical statistics.
• Invited speaker at several scientific events. Undertook research visits as a visiting scholar at the Department of Statistics, University of Warwick.
• Active research collaborations nationally and internationally.
• Published in leading statistics journals, including Journal of the Royal Statistical Society (Series B and C), Biometrika, Journal of the American Statistical Association, Journal of Computational and Graphical Statistics, and Statistics and Computing.
• Supervised and co-supervised several PhD and MSc students.
• Recipient of competitive research grants in Brazil.
• Former President of the Brazilian Chapter of the International Society for Bayesian Analysis (ISBrA).
• Current research focuses on modern Monte Carlo methods, including infinite-dimensional MCMC, Gaussian process models, and scalable Bayesian computation.

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