Galit Shmueli is Tsing Hua Distinguished Professor at the Institute of Service Science, College of Technology Management, National Tsing Hua University, Taiwan. Earlier she was Associate Professor at University of Maryland's Smith School of Business, and then the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business.
Dr. Shmueli’s research focuses on statistical and machine learning methodology with applications in information systems and healthcare, and an emphasis on human behavior. She authors multiple books, including the popular textbook Data Mining for Business Analytics and over 100 publications in peer-reviewed journals and books, including Management Science, Journal of the American Statistical Association, Journal of the Royal Statistical Society, Information Systems Research, MIS Quarterly, Marketing Science, Statistical Science and Technometrics. Dr. Shmueli is a frequent speaker at conferences and seminars, and has won prestigious research awards.
Dr. Shmueli is the inaugural Editor-in-Chief of the INFORMS Journal on Data Science, and has served on editorial boards of top journals in statistics and information systems (e.g. Decision Sciences Journal, Annals of Applied Statistics, Statistical Science, MIS Quarterly, JASA Reviews & The American Statistician Reviews). She has chaired and served on many program committees of top conferences and workshops. She is an IMS Fellow and ISI elected member.
After graduating from the Technion – Israel Institute of Technology in 2000, Dr. Shmueli was Visiting Assistant Professor at Carnegie Mellon University’s Statistics Department, where she first became involved in early biosurveillance research and efforts. Dr. Shmueli’s work in biosurveillance, BioSense Initiative to Improve Early Event Detection, in collaboration with the Johns Hopkins Applied Physics Lab received a 3-year award from the Centers for Disease Control & Prevention. Her co-authored 2010 paper “Statistical Challenges Facing Early Outbreak Detection in Biosurveillance” was the featured article in Technometrics. She has also been involved in data mining methods for improving kidney allocation.
Dr. Shmueli’s work in information systems started in 2002, when joining University of Maryland’s Robert H Smith School of Business. Her work focuses on electronic commerce and online auctions. In 2004, Dr. Shmueli co-founded the now annual symposium Statistical Challenges in eCommerce Research. Her research focuses on applying novel statistical methodology and adapting existing methods for modern data structures. Her papers “To Explain or To Predict?” and “Predictive Analytics in Information Systems Research” have attracted much attention and won several research and “best paper” awards.
Dr. Shmueli teaches courses on data mining, forecasting analytics, interactive visualization, research methods, and other business analytics topics. Her online teaching videos are highly subscribed. She has experience in teaching engineers and business students, undergraduate and graduate students, teaching online and on-ground. Dr. Shmueli has won multiple teaching awards, and has supervised many students.