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Sir David Roxbee Cox was a British statistician and educator. His wide-ranging contributions to the field of statistics included introducing logistic regression, the proportional hazards model and the Cox process, a point process named after him.
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.
Sir David John Spiegelhalter is a British statistician and a Fellow of Churchill College, Cambridge. From 2007 to 2018 he was Winton Professor of the Public Understanding of Risk in the Statistical Laboratory at the University of Cambridge. Spiegelhalter is an ISI highly cited researcher.
Hirotsugu Akaike was a Japanese statistician. In the early 1970s, he formulated the Akaike information criterion (AIC). AIC is now widely used for model selection, which is commonly the most difficult aspect of statistical inference; additionally, AIC is the basis of a paradigm for the foundations of statistics. Akaike also made major contributions to the study of time series. As well, he had a large role in the general development of statistics in Japan.
Sir Bernard Walter Silverman, is a British statistician and former Anglican clergyman. He was Master of St Peter's College, Oxford, from 1 October 2003 to 31 December 2009. He is a member of the Statistics Department at Oxford University, and has also been attached to the Wellcome Trust Centre for Human Genetics, the Smith School of Enterprise and the Environment, and the Oxford-Man Institute of Quantitative Finance. He has been a member of the Council of Oxford University and of the Council of the Royal Society. He was briefly president of the Royal Statistical Society in January 2010, a position from which he stood down upon announcement of his appointment as Chief Scientific Adviser to the Home Office. He was awarded a knighthood in the 2018 New Years Honours List, "For public service and services to Science".
Mir Masoom Ali is a Bangladeshi American statistician, Distinguished Professor, educator, researcher and author. He migrated to the United States in 1969 and became a naturalized citizen in 1981. Ali founded the graduate and undergraduate programs in statistics at Ball State University. He co-founded the Midwest Biopharmaceutical Statistics Workshop (MBSW-History), held at Ball State University annually since 1978, and co-sponsored by the American Statistical Association. He served as editor and associate editor of several international statistical journals. He is the founding president of the North America Bangladesh Statistical Association (NABSA) and a member of advisory board at Shahjalal University of Science and Technology in Sylhet, Bangladesh. In 2002 Ali received the Sagamore of the Wabash Award, the highest award given in the US state of Indiana, by the Governor of Indiana Frank O'Bannon, for his contributions to Ball State University, to higher education in the state, and specifically to the statistics profession.
Howell Tong is a statistician who has made fundamental contributions to nonlinear time series analysis, semi-parametric statistics, non-parametric statistics, dimension reduction, model selection, likelihood-free statistics and other areas. In the words of Professor Peter Whittle (FRS): "The striking feature of Howell Tong's … is the continuing freshness, boldness and spirit of enquiry which inform them-indeed, proper qualities for an explorer. He stands as the recognised innovator and authority in his subject, while remaining disarmingly direct and enthusiastic." His work, in the words of Sir David Cox, "links two fascinating fields, nonlinear time series and deterministic dynamical systems." He is the father of the threshold time series models, which have extensive applications in ecology, economics, epidemiology and finance. Besides nonlinear time series analysis, he was the co-author of a seminal paper, which he read to the Royal Statistical Society, on dimension reduction in semi-parametric statistics by pioneering the approach based on minimum average variance estimation. He has also made numerous novel contributions to nonparametric statistics, Markov chain modelling, reliability, non-stationary time series analysis and wavelets.
Richard John Samworth is the Professor of Statistical Science and the Director of the Statistical Laboratory, University of Cambridge, and a Teaching Fellow of St John's College, Cambridge. He was educated at St John's College, Cambridge. His main research interests are in nonparametric and high-dimensional statistics. Particular topics include shape-constrained density estimation and other nonparametric function estimation problems, nonparametric classification, clustering and regression, the bootstrap and high-dimensional variable selection problems.
Chien-Fu Jeff Wu is the Coca-Cola Chair in Engineering Statistics and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. He is known for his work on the convergence of the EM algorithm, resampling methods such as the bootstrap and jackknife, and industrial statistics, including design of experiments, and robust parameter design.
Jianqing Fan is a statistician, financial econometrician, and data scientist. He is currently the Frederick L. Moore '18 Professor of Finance, Professor of Operations Research and Financial Engineering, Professor of Statistics and Machine Learning, and a former Chairman of Department of Operations Research and Financial Engineering (2012–2015) and a former director of Committee of Statistical Studies (2005–2017) at Princeton University, where he directs both statistics lab and financial econometrics lab since 2008.
Robert Tibshirani is a professor in the Departments of Statistics and Biomedical Data Science at Stanford University. He was a professor at the University of Toronto from 1985 to 1998. In his work, he develops statistical tools for the analysis of complex datasets, most recently in genomics and proteomics.
Trevor John Hastie is an American statistician and computer scientist. He is currently serving as the John A. Overdeck Professor of Mathematical Sciences and Professor of Statistics at Stanford University. Hastie is known for his contributions to applied statistics, especially in the field of machine learning, data mining, and bioinformatics. He has authored several popular books in statistical learning, including The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Hastie has been listed as an ISI Highly Cited Author in Mathematics by the ISI Web of Knowledge. He also contributed to the development of S.
Raymond James Carroll is an American statistician, and Distinguished Professor of statistics, nutrition and toxicology at Texas A&M University. He is a recipient of 1988 COPSS Presidents' Award and 2002 R. A. Fisher Lectureship. He has made fundamental contributions to measurement error model, nonparametric and semiparametric modeling.
Marvin Zelen was Professor Emeritus of Biostatistics in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health (HSPH), and Lemuel Shattuck Research Professor of Statistical Science. During the 1980s, Zelen chaired HSPH's Department of Biostatistics. Among colleagues in the field of statistics, he was widely known as a leader who shaped the discipline of biostatistics. He "transformed clinical trial research into a statistically sophisticated branch of medical research."
Grace Yun Yi is a professor of the University of Western Ontario where she currently holds a Tier I Canada Research Chair in Data Science. She was a professor at the University of Waterloo, Canada, where she holds a University Research Chair in Statistical and Actuarial Science. Her research concerns event history analysis with missing data and its applications in medicine, engineering, and social science.
Dipak Kumar Dey is an Indian-American statistician best known for his work on Bayesian methodologies. He is currently the Board of Trustees Distinguished Professor in the Department of Statistics at the University of Connecticut. Dey has an international reputation as a statistician as well as a data scientist. Since he earned a Ph.D. degree in statistics from Purdue University in 1980, Dey has made tremendous contributions to the development of modern statistics, especially in Bayesian analysis, decision science and model selection. Dey has published more than 10 books and edited volumes, and over 260 research articles in peer-refereed national and international journals. In addition, the statistical methodologies that he has developed has found wide applications in a plethora of interdisciplinary and applied fields, such as biometry and bioinformatics, genetics, econometrics, environmental science, and social science. Dey has supervised 40 Ph.D. students, and presented more than 200 professional talks in colloquia, seminars and conferences all over the world. During his career, Dey has been a visiting professor or scholar at many institutions or research centers around the world, such as Macquarie University, Pontificia Universidad Católica de Chile,, University of São Paulo, University of British Columbia, Statistical and Applied Mathematical Sciences Institute, etc. Dey is an elected fellow of the American Association for the Advancement of Science, the American Statistical Association, the Institute of Mathematical Statistics, the International Society for Bayesian Analysis and the International Statistical Institute.
Cynthia Diane Rudin is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning. She is the director of the Interpretable Machine Learning Lab at Duke University, where she is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics and bioinformatics. In 2022, she won the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI) for her work on the importance of transparency for AI systems in high-risk domains.
Peter Lukas Bühlmann is a Swiss mathematician and statistician.
Yingying Fan is a Chinese-American statistician and Centennial Chair in Business Administration and Professor in Data Sciences and Operations Department of the Marshall School of Business at the University of Southern California. She is currently the Associate Dean for the PhD Program at USC Marshall. She also holds joint appointments at the USC Dana and David Dornsife College of Letters, Arts and Sciences, and Keck Medicine of USC. Her contributions to statistics and data science were recognized by the Royal Statistical Society Guy Medal in Bronze in 2017 and the Institute of Mathematical Statistics Medallion Lecture in 2023. She was elected Fellow of American Statistical Association in 2019 and Fellow of Institute of Mathematical Statistics for seminal contributions to high-dimensional inference, variable selection, classification, networks, and nonparametric methodology, particularly in the field of financial econometrics, and for conscientious professional service in 2020.
Hongmei Zhang is a Chinese-American biostatistician at the University of Memphis, where she is Bruns Endowed Professor in the Division of Epidemiology, Biostatistics, and Environmental Health Sciences, director of the division, program coordinator for biostatistics, and affiliated professor in the departments of mathematical sciences and biology. Her statistical interests include feature selection, biclustering, and Bayesian networks; she is also interested in the application of statistical methods to phenotype and genetic data and to epigenetics.
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