徐茉莉 Galit Shmueli

Galit Shmueli
Distinguished Professor
  • Business analytics
  • Statistical and data mining methodology
  • Big Data
  • Online markets

Brief Bio

現職 Employment 
  • Distinguished Professor, Institute of Service Science, National Tsing Hua University, Taiwan 
  • SRITNE Chaired Professor of Data Analytics; Tenured Associate Professor of Statistics & Information Systems, Indian School of Business, Hyderabad, India
  • Tenured Associate Professor of Statistics, Department of Decision, Operations & Information Technologies, Robert H. Smith School of Business, University of Maryland, College Park MD, USA
  • Assistant Professor of Statistics, Department of Decision, Operations & Information Technologies, Robert H. Smith School of Business, University of Maryland, College Park MD, USA
  • Visiting Assistant Professor, Department of Statistics, Carnegie Mellon University, Pittsburgh PA, USA
學歷 Education 
  • PhD, Statistics, Faculty of Industrial Engineering & Management, Technion, Israel
  • MSc, Statistics, Faculty of Industrial Engineering & Management, Technion, Israel
  • BA, Statistics & Psychology, Summa cum Laude, Haifa University, Israel
研究興趣 Research Interests 
  • Statistical methodology and data mining for real-world applications
  • Statistical strategy:  empirical modeling for scientific research
  • Business analytics
  • Models for contemporary data structures
  • Anomaly detection

Select Publications

    1. Yahav, I., Shmueli, G. and Mani, D. (2016) “A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Big Data”, MIS Quarterly, forthcoming.
    2. Bapna, R., Ramprasad, J., Shmueli, G. and Umyarov, A., (2016), “One-Way Mirrors and Weak-Signaling in Online Dating: A Randomized Field Experiment”, Management Science, forthcoming.
    3. Kenett, R. S. and Shmueli, G. (2014), “On Information Quality”, with discussion and rejoinder, Journal of the Royal Statistical Society, Series A, vol 177(1), pp. 3-38.
    4. Lin, M., Lucas, H., and Shmueli, G. (2013) “Too Big To Fail: Larger Samples and the P-Value Problem”, Information Systems Research, vol 24 (4), pp. 906-917.
    5. Sellers, K. F., Borle, S., and Shmueli, G. (2012) “The COM-Poisson Model for Count Data: A Survey of Methods and Applications”, Applied Stochastic Models in Business and Industry, vol 28 (2), pp. 104-116; Rejoinder pp. 128-129.
    6. Shmueli, G. and Koppius, O. (2011) “Predictive Analytics in Information Systems Research”, MIS Quarterly, vol 35 no 3, pp. 553-572.
    7. Shmueli, G. (2010), “To Explain or To Predict?”, Statistical Science, vol 25(3), pp. 289-310.  
    8. Bapna, R., Jank, W. and Shmueli, G., (2008) “Consumer Surplus in Online Auctions”, Information Systems Research, vol. 19(4), pp. 400 - 416. 
    9. Shmueli, G., Minka, T. P., Kadane, J. B., Borle, S. and Boatwright, P. (2005), “A Useful Distribution for Fitting Discrete Data: Revival of the COM-Poisson”, Journal of the Royal Statistical Society, Series C (Applied Statistics), vol 54 no 1, pp. 127-142.

    Teaching

    http://dataminingbook.com

    http://www.forecastingbook.com

    Recent Awards

    2016 E.SUN Bank Academic Award, Taiwan

    2013 Excellence in Teaching Award, Indian School of Business, India

    2012 Winner of the Greenfield Challenge, European Network for Business and Industrial Statistics

    2012 Best Faculty Award, The Rigsum Institute of IT and Management, Bhutan

    2009 Best Information Systems Publication of 2008 Award, Association for Information Systems (AIS)

    2008 Top 15% teaching award, Smith School of Business, University of Maryland