Dr Shirley Y Coleman
Shirley Coleman is Technical Director of NU Solve, working in business engagement in the school of Mathematics, Statistics and Physics at Newcastle University, UK. She is a council member of the Royal Statistical Society and chairs the Discussion Meetings Committee. She is a former President of the European Network of Business and Industrial Statistics where she chairs ukENBIS and the Statistics in Practice special interest group. She is co-author (with Andrea Ahlemeyer-Stubbe) of ‘Monetising Data — How to Uplift Your Business’ and ‘A Practical Guide to Data Mining for Business and Industry’. Her focus is on statistics and data science applications and she works with small to medium enterprises (SMEs) in knowledge exchange partnerships.
Professor Mark Girolami is the Chief Scientist of The Alan Turing Institute, the UK’s National Institute for data science and artificial intelligence and took up this role in October 2021. He was one of the original founding Executive Directors of the Institute and previous to his role as Chief Scientist he led the Turing’s Data-Centric Engineering programme, which is principally funded by Lloyd’s Register Foundation. In 2019, Mark was elected to the Sir Kirby Laing Professorship of Civil Engineering at the University of Cambridge where he also holds the Royal Academy of Engineering Research Chair in Data Centric Engineering. Prior to joining the University of Cambridge, he held the Chair of Statistics in the Department of Mathematics at Imperial College London. He is an elected fellow of the Royal Academy of Engineering and the Royal Society of Edinburgh, he was an EPSRC Advanced Research Fellow (2007-2012), an EPSRC Established Career Research Fellow (2012-2018), and a recipient of a Royal Society Wolfson Research Merit Award. He delivered the IMS Medallion Lecture at the Joint Statistical Meeting 2017, and the Bernoulli Society Forum Lecture at the European Meeting of Statisticians 2017, he delivered the BCS and IET Turing Talk in London, Manchester, and Belfast in 2020, and in 2023 was awarded the Royal Statistical Society Guy Medal in Silver. Professor Girolami spent ten years with IBM prior to starting his academic career.
Robert Gramacy is a Professor of Statistics at Virginia Tech, and a Fellow of the American Statistical Association (ASA). He currently serves as the Editor-in-chief at Technometrics, an ASA journal, and as President for the ASA's Uncertainty Quantification Interest Group. Recently he completed tours as President of the ASA's Section on Physical and Engineering Sciences, and as Treasurer for the International Society of Bayesian Analysis. Robert works mainly on surrogate modeling, uncertainty quantification (UQ), Bayesian inference and statistical computing.
Marco ReisMarco S. Reis is an Associate Professor with Habilitation of Chemical Engineering at the University of Coimbra, Portugal. His research interests include process systems engineering, industrial data science, sensor fusion, hybrid modelling, fault detection/diagnosis/prognosis, predictive analytics, structured process improvement and chemometrics. He was President of the European Network for Business and Industrial Statistics (ENBIS) (2015-2017) and is currently an Honorary Member of this society. He was awarded with the Fulbright scholar fellowship (2020) and is the recipient of the Professor Almiro e Castro Award which distinguishes the scientific merit of a Portuguese researcher or faculty under 45 years old (2018). He is a member of the Editorial Boards of Chemometrics and Intelligent Laboratory Systems and Processes, Associate Editor of Statistical Papers, and Member of the International Advisory Panel of Chemical Engineering Science; he was a member of the Editorial Board of Quality Engineering.
Steven E. Rigdon is Professor of Biostatistics in the Department of Epidemiology and Biostatistics at Saint Louis University. He is also Distinguished Research Professor Emeritus of statistics at Southern Illinois University Edwardsville. He is a Fellow of the American Statistical Association and has received the Vizeau Award from the St. Louis Section of ASQ, the Paul Simon Teaching/Research Award from SIUE, and the Soren Bisgaard Award (2020). He is the author of Calculus (along with D. Varberg and E. Purcell, 2007), Statistical Methods for the Reliability of Repairable Systems (with Asit Basu, 2000), Design of Experiments for Reliability Achievement (with Rong Pan, Doug Montgomery, and Laura Freeman, 2022), Monitoring the Health of Populations by Tracking Disease Outbreaks (with Ron Fricker, 2020), and Introduction to Probability, Statistics, and Data Science (with Ron Fricker and Doug Montgomery, 2023). He is past editor of Journal of Quantitative Analysis in Sports, and currently serves on the editorial board of Journal of Quality Technology and Journal of Quantitative Analysis in Sports.
Dr. Joanne Wendelberger has been a statistician at Los Alamos National Laboratory since 1992. She served as an R&D Manager for the Statistical Sciences Group and the Computer, Computation, and Statistical Sciences Division from 2005-2016 prior to returning to full time technical work in her current position as a senior level Scientist. She completed her Masters and Ph.D. degrees in Statistics at the University of Wisconsin-Madison, where she was a student of Professor George Box. She received her Bachelor’s Degree from Oberlin College, majoring in Mathematics and Economics. She previously worked as a Statistical Consultant at the General Motors Research Laboratories. Throughout her career, Dr. Wendelberger’s research has been motivated by the need to develop solutions to complex interdisciplinary problems, particularly in the physical and engineering sciences. Her research interests include statistical experimental design and test planning, statistical bounding and error analysis, materials degradation modeling, analysis of discrete simulations, sampling and analysis for large-scale computation and visualization, functional data analysis, and institutional analytics. Her publications have included work on orthogonal and near-orthogonal designs, uncertainty in designed experiments, repeated measures degradation studies, metrology, randomized selection on the GPU, data sampling using bitmap indexing, in situ sampling of a large-scale particle simulation, and colormaps for improving data perception. Dr. Wendelberger is a Fellow of the American Statistical Association and a Senior Member of the American Society for Quality which has recognized her as the W J. Youden Memorial Address lecturer at the Fall Technical Conference and as recipient of the William G. Hunter Award. She is currently an Associate Editor for Technometrics and has previously served as a member of the Technometrics Management Committee as well as numerous conference and awards committees. She has also mentored students at Los Alamos National Laboratory and shared her knowledge of Statistics at a variety of K-12 educational outreach activities.