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| Matteo Viel | |
|---|---|
| Name | Matteo Viel |
| Occupation | Academic, Researcher |
| Known for | Research in statistical methodology, biostatistics, Bayesian inference |
Matteo Viel is an Italian statistician and academic known for contributions to statistical methodology, Bayesian computation, and applications in epidemiology and genetics. He has held positions at leading European and international research institutions and collaborated with researchers across disciplines including public health, bioinformatics, and environmental science. Viel's work bridges theoretical developments in probability and practical implementations in data analysis, influencing methods used in clinical trials, infectious disease modeling, and large-scale genomic studies.
Viel was born and raised in Italy, where he completed early schooling before pursuing higher education at prominent Italian institutions. He obtained degrees from universities known for mathematics and statistics, engaging with scholars affiliated with Sapienza University of Rome, University of Padua, University of Bologna, and research networks connected to the Istituto Nazionale di Statistica. During his formative years he trained under supervisors with links to the European Molecular Biology Laboratory and the Istituto Superiore di Sanità, developing skills in probability theory, computational statistics, and applied biostatistics. His doctoral work involved collaborations with groups active at the University of Cambridge and exchange visits to centers like the Max Planck Society and the École Polytechnique Fédérale de Lausanne.
Viel's academic appointments span universities and research institutes across Italy and Europe. He has held faculty and research positions connected to the University of Padua, University of Milan, and collaborations with the Karolinska Institutet and University College London. Viel has been involved with interdisciplinary centers such as the European Bioinformatics Institute and national research agencies including the Istituto Nazionale di Ricerca Metrologica (INRIM) and the Consiglio Nazionale delle Ricerche. He served on doctoral and postdoctoral committees at institutions like the University of Oxford and the Politecnico di Milano, and participated in European Commission-funded projects coordinated through the Horizon 2020 framework. Viel has taught courses in statistical inference, computational statistics, and biostatistics at undergraduate and graduate levels, supervising students who later joined research groups at the Wellcome Trust Sanger Institute and the European Centre for Disease Prevention and Control.
Viel's research spans methodological advances and applied statistical modeling. In methodological areas he developed approaches in Bayesian computation, Markov chain Monte Carlo methods, and approximate Bayesian computation with applications to high-dimensional inference, collaborating with teams at the Alan Turing Institute and the National Institute of Statistical Sciences. He contributed to model selection techniques used in longitudinal and survival analysis employed by researchers at the European Society for Clinical Investigation and the International Biometric Society. Viel's work in infectious disease modeling informed studies linked to the European Centre for Disease Prevention and Control and national public health agencies, applying hierarchical models and time-series methods to outbreak data from epidemics studied by the World Health Organization and the Centers for Disease Control and Prevention. In genetics and genomics, he developed statistical tools for association studies and population structure inference used in consortia such as the 1000 Genomes Project, the International HapMap Project, and collaborations with the Wellcome Trust. Viel's cross-disciplinary projects included environmental statistics collaborations with the European Environment Agency and spatial modeling tied to research at the University of Copenhagen and the Swiss Federal Institute of Technology in Zurich.
Viel received recognition from national and international bodies for his contributions to statistics and interdisciplinary research. Honors include fellowships and prizes connected to the European Research Council, awards from the Italian Statistical Society (SIS), and grants under the Marie Skłodowska-Curie Actions. He has been invited to present keynote lectures at conferences organized by the International Biometric Society, the Royal Statistical Society, and the Institute of Mathematical Statistics. Viel has held visiting scholar appointments at the Massachusetts Institute of Technology, the University of California, Berkeley, and research fellowships associated with the European Molecular Biology Laboratory.
Viel authored and co-authored papers in leading journals and contributed chapters to edited volumes. Representative publications include methodological papers in journals such as the Journal of the Royal Statistical Society, Series B, Biometrika, and Annals of Applied Statistics; applied studies in PLOS Computational Biology, Nature Communications, and Lancet Infectious Diseases; and collaborative genomics contributions appearing in Nature Genetics and Genome Research. He also contributed to methodological handbooks published by the Oxford University Press and the Springer Nature series on computational statistics.
Outside academia, Viel has participated in science communication and public engagement initiatives with organizations like the European Researchers' Night and national science festivals in Italy coordinated with the Istituto Nazionale di Astrofisica and cultural institutions such as the Biblioteca Nazionale Centrale di Firenze. He has served on advisory panels for public research funding bodies and contributed to open-source statistical software used by communities around projects hosted by the R Foundation for Statistical Computing, GitHub, and collaborative platforms supported by the European Open Science Cloud.
Category:Italian statisticians