Alicia Carriquiry is Distinguished Professor of Statistics and Director of the Center for Statistics and Applications in Forensic Science at Iowa State University. She works in linear models and Bayesian statistics. She is a Fellow of the Institute of Mathematical Statistics (2006) and the American Statistical Association (1999) and has served on numerous committees for the National Academy of Sciences.
René Carmona is the Paul M. Wythes ’55 Professor of Engineering and Finance at Princeton University, the Director of Graduate Studies in the Bendheim Center for Finance, and former Chair of the Operations Research and Financial Engineering Department and member of the Program in Applied and Computational Mathematics. He works in stochastic analysis, financial mathematics, and statistical data analysis. He was elected Fellow of the Institute of Mathematical Statistics, of the Society for Industrial and Applied Mathematics, and of the American Mathematical Society. He served on the Board of the Institute for Mathematics and Its Applications, and of the Oxford Man Institute. In January 2020, he was awarded the Doob Prize from the American Mathematical Society.
Amir Dembo is the Marjorie Mhoon Fair Professor of Quantitative Science and Professor of Mathematics and Statistics at Stanford University. He works in probability theory, information theory, and stochastic processes. He is a Fellow of the Institute of Mathematical Statistics and served on the Board of the Institute for Mathematics and Its Applications from 2012–2017.
Bjorn Engquist is Professor and Chair of Computational and Applied Mathematics and Director of the Oden Institute for Computational Engineering and Sciences Center for Numerical Analysis at the University of Texas at Austin. He works on the development and analysis of numerical methods for differential equations. Engquist is a member of the Royal Swedish Academy of Sciences, the Royal Swedish Academy of Engineering Sciences, and the Norwegian Academy of Science and Letters. He was a Guggenheim Fellow, and received the first James H. Wilkinson Prize in Numerical Analysis and Scientific Computing in 1982, as well as the Henrici Prize in 2011.
Thomas Grandine was a Senior Technical Fellow at The Boeing Company and holds a PhD in Numerical Analysis from the University of Wisconsin at Madison. His areas of expertise include advanced geometric design, curve and surface modeling, numerical approximation, splines, and multidisciplinary design optimization. He is a Fellow of the Society for Industrial and Applied Mathematics and is currently a member of the Board of Trustees.
Larry Hedges is a Board of Trustees Professor of Statistics and Chair, of the Department of Statistics at Northwestern University. He works in applied statistics and applications of statistics in social policy analysis. He is currently the Chair of the US National Education Sciences Board where he was appointed in 2012 by President Obama. He is an elected member of the National Academy of Education and is a fellow of the American Academy of Arts and Sciences, the American Statistical Association, the American Psychological Association, and the American Educational Research Association. He received the Yidan Prize in Education Research in 2018.
Claude Le Bris is a research scientist at the École des Ponts and Inria, Paris, where he holds positions as Civil Engineer-General and scientific leader of the MATHERIALS research team. His research has focused on mathematical analysis and numerical methods for partial differential equations, with contributions in several areas including the mathematics of physics and materials science, and multiscale problems. Le Bris’ list of honors includes the Blaise Pascal Prize 1999 from the French Academy of Sciences and the Giovanni Sacchi-Landriani Prize 2002 from the Lombard Academy of Arts and Sciences. In Madrid 2006, he gave an invited lecture at the ICM and in Valencia 2019, an invited lecture at the ICIAM. He serves on several scientific advisory boards for research institutes and private companies, and has extensive editorial responsibilities for book series and journals.
Rebecca Willett is Professor of Statistics and Computer Science at the University of Chicago. Her research interests include signal processing, machine learning, and large-scale data science. She received the National Science Foundation CAREER Award in 2007, was a member of the DARPA Computer Science Study Group from 2007 to 2011, and received an Air Force Office of Scientific Research Young Investigator Program award in 2010.
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