Fabrizio Ruggeri is an Italian statistician. He is a research director at the National Research Council Istituto di matematica applicata e tecnologie informatiche (CNR-IMATI) in Milan, Italy. His work focusses on Bayesian methods, specifically robustness and stochastic process inference. He has done innovative work on the sensitivity of Bayesian methods and incompletely specified priors. He has worked on Bayesian wavelet methods, and on a vast variety of applications to industrial problems. His publications include well over 150 refereed papers and book chapters, as well as five books.
Ruggeri was born in Reggio nell'Emilia in northern Italy. He received his B.Sc. in mathematics at the University of Milan in 1982. From 1983 to 1988, he took on a series of jobs in the industry. He moved to the US to continue study in 1988, receiving a M.Sc. in statistics from Carnegie Mellon University in 1989, and his PhD in statistics from Duke University in 1994. [1] Ruggeri was an adjunct faculty member at the Polytechnic University of Milan between 1995 and 2003. He was faculty in Ph.D. program in Mathematics at the University of Pavia from 1999 to 2015 and from 2015 to 2024 he was faculty at the joint Ph.D. program in Mathematics of the University of Pavia and the University of Milano-Bicocca. [2]
Ruggeri is an elected member of the International Statistical Institute [3] and a fellow of the American Statistical Association, [4] the International Society for Bayesian Analysis [5] (ISBA) and the Institute of Mathematical Statistics. [6] He is the first recipient of the Zellner Medal [7] by ISBA. He was the president of the International Society for Bayesian Analysis in 2012 and the European Network for Business and Industrial Statistics [8] in 2005–6, and is currently President of the International Society for Business and Industrial Statistics and vice-president of the International Statistical Institute. He is Editor-in-Chief of Applied Stochastic Models in Business and Industry and of Statistics Reference Online.[ citation needed ]
Stephen Elliott Fienberg was a professor emeritus in the Department of Statistics, the Machine Learning Department, Heinz College, and Cylab at Carnegie Mellon University. Fienberg was the founding co-editor of the Annual Review of Statistics and Its Application and of the Journal of Privacy and Confidentiality.
Arnold Zellner was an American economist and statistician specializing in the fields of Bayesian probability and econometrics. Zellner contributed pioneering work in the field of Bayesian analysis and econometric modeling.
The International Society for Bayesian Analysis (ISBA) is a society with the goal of promoting Bayesian analysis for solving problems in the sciences and government. It was formally incorporated as a not for profit corporation by economist Arnold Zellner and statisticians Gordon M. Kaufman and Thomas H. Leonard on 10 November 1992. It publishes the electronic journal Bayesian Analysis and organizes world meetings every other year.
The Institute of Mathematical Statistics is an international professional and scholarly society devoted to the development, dissemination, and application of statistics and probability. The Institute currently has about 4,000 members in all parts of the world. Beginning in 2005, the institute started offering joint membership with the Bernoulli Society for Mathematical Statistics and Probability as well as with the International Statistical Institute. The Institute was founded in 1935 with Harry C. Carver and Henry L. Rietz as its two most important supporters. The institute publishes a variety of journals, and holds several international conference every year.
Morris Herman DeGroot was an American statistician.
José-Miguel Bernardo Herranz is a Spanish mathematician and statistician. He is a noted Bayesian and known for introducing the concept of reference priors.
Donald Jay Geman is an American applied mathematician and a leading researcher in the field of machine learning and pattern recognition. He and his brother, Stuart Geman, are very well known for proposing the Gibbs sampler and for the first proof of the convergence of the simulated annealing algorithm, in an article that became a highly cited reference in engineering. He is a professor at the Johns Hopkins University and simultaneously a visiting professor at École Normale Supérieure de Cachan.
David Ríos Insua is a Spanish mathematician, and son and disciple of Sixto Ríos, the "father of Spanish statistics." He is currently also the youngest Fellow of the Spanish Royal Academy of Sciences, which he joined in 2008. He received a PhD in Computational Sciences at the University of Leeds. He is Full Professor of the Statistics and Operations Research Department at Rey Juan Carlos University (URJC), and he has been Vice-dean of New Technologies and International Relationships at URJC (2002–2009). He has worked in fields such as Bayesian inference in neuronal networks, MCMC methods in decision analysis, Bayesian robustness or adversarial risk analysis. He has also worked in applied areas such as Electronic Democracy, reservoirs management, counterterrorism model and many others. He is married and has two daughters.
In statistics, robust Bayesian analysis, also called Bayesian sensitivity analysis, is a type of sensitivity analysis applied to the outcome from Bayesian inference or Bayesian optimal decisions.
Stuart Alan Geman is an American mathematician, known for influential contributions to computer vision, statistics, probability theory, machine learning, and the neurosciences. He and his brother, Donald Geman, are well known for proposing the Gibbs sampler, and for the first proof of convergence of the simulated annealing algorithm.
Kerrie Mengersen is an Australian statistician, distinguished Professor of Statistics at Queensland University of Technology, and 2024 winner of the Ruby Payne-Scott Medal and Lecture from the Australian Academy of Science.
Alan Enoch Gelfand is an American statistician, and is currently the James B. Duke Professor of Statistics and Decision Sciences at Duke University. Gelfand’s research includes substantial contributions to the fields of Bayesian statistics, spatial statistics and hierarchical modeling.
Merlise Aycock Clyde is an American statistician known for her work in model averaging for Bayesian statistics. She is a professor of Statistical Science and immediate past chair of the Department of Statistical Science at Duke University. She was president of the International Society for Bayesian Analysis (ISBA) in 2013, and chair of the Section on Bayesian Statistical Science of the American Statistical Association for 2018.
Amy Helen Herring is an American biostatistician interested in longitudinal data and reproductive health. Formerly the Carol Remmer Angle Distinguished Professor of Children's Environmental Health at the University of North Carolina at Chapel Hill, she is now Sara & Charles Ayres Distinguished Professor in the Department of Statistical Science, Global Health Institute, and Department of Biostatistics & Bioinformatics of Duke University.
Judith Rousseau is a Bayesian statistician who studies frequentist properties of Bayesian methods. She is a professor of statistics at the University of Oxford, a Fellow of Jesus College, Oxford, a Fellow of the Institute of Mathematical Statistics, and a Fellow of the International Society for Bayesian Analysis.
Sonia Petrone is an Italian mathematical statistician, known for her work in Bayesian statistics, including use of Bernstein polynomials for nonparametric methods in Bayesian statistics.[RBP][BDE][CPP] With Patrizia Campagnoli and Giovanni Petris she is the author of the book Dynamic Linear Models with R .[DLM]
Victor Michael Panaretos is a Greek mathematical statistician. He is currently Professor and Director at the Institute of Mathematics of the École Polytechnique Fédérale de Lausanne (EPFL), where he holds the chair of Mathematical Statistics.
Christian P. Robert is a French statistician, specializing in Bayesian statistics and Monte Carlo methods.
Mike West is an English and American statistician. West works primarily in the field of Bayesian statistics, with research contributions ranging from theory to applied research in areas including finance, commerce, macroeconomics, climatology, engineering, genomics and other areas of biology. Since 1999, West has been the Arts & Sciences Distinguished Professor of Statistics & Decision Sciences in the Department of Statistical Science at Duke University.
Steve MacEachern is an American Statistician. MacEachern is a Distinguished Arts & Sciences Professor of Statistics at the Ohio State University. He received his B.A. in Mathematics from Carleton College in 1982 and his Ph.D. in Statistics from the University of Minnesota in 1988. His doctoral work focused on nonparametric Bayesian methods under the guidance of Don Berry. MacEachern joined the faculty at Ohio State in 1988 and has been a member of the Department of Statistics ever since. He has a courtesy appointment as a Professor in the Department of Psychology. He is best known for Bayesian modeling and computation, with a particular emphasis on dependent Dirichlet processes. He has published extensively in leading statistical journals, and his work has had a significant impact on the field. He is also the advisor of esteemed professor William Francis Darnieder.