Galit Shmuéli
homepage:http://galitshmueli.com/content/won-greenfield-challenge?utm_source=twitterfeed&utm_medium=facebook
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Description

Galit Shmueli is 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 data mining methodology with applications in information systems and healthcare. She authors five books, including the popular textbook Data Mining for Business Intelligence and over 50 publications in peer-reviewed journals and books, including the top journals Management Science, Journal of the American Statistical Association, Journal of the Royal Statistical Society, Information Systems Research, MISQ, Marketing Science, Statistical Science and Technometrics. She has presented her work at multiple venues in the US and internationally.

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, statistics, and other business analytics topics. 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 supervised several Masters and PhD students.

Dr. Shmueli is associate editor for the top journals Annals of Applied Statistics, JASA & The American Statistician Reviews and was guest editor of a special issue of Statistical Science. She has served on many program committees of top conferences and workshops. In addition to her academic work, Dr. Shmueli has provided consulting services to private companies (including Pricewaterhouse Coopers, Structured Decisions Corporation, and Accenture) and to US government and state agencies (including the Environmental Protection Agency (EPA) and Indiana Economic Development Corporation).


Lecture:

lecture
flag A Flexible Model for Count Data: The COM-Poisson Distribution
as author at  Solomon seminar,
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