徐茉莉 Galit Shmueli

Distinguished Professor

galit.shmueli@iss.nthu.edu.tw

www.galitshmueli.com

Full CV

  • Business analytics

  • Statistical and data mining methodology

  • Behavioral 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

  • Behavioral big data

Select Publications

  1. Tafti, A. R. and Shmueli, G. (2020), "Beyond overall treatment effects: Leveraging covariates in randomized experiments guided by causal structure", Information Systems Research, forthcoming.

  2. Ashouri, M., Shmueli, G., and Sin, C. Y. (2019), Tree-based Methods for Clustering Time Series Using Domain-Relevant Attributes, Journal of Business Analytics, vol. 2 no. 1, pp. 1-23.

  3. Sharma, P., Sarstedt, M., Shmueli, G., and Thiele, K. O. (2019), PLS-Based Model Selection: The Role of Alternative Explanations in MIS Research, Journal of the Association for Information Systems (JAIS), vol 20 no 4, Article 4.

  4. Shmueli, G. and Yahav, I. (2018), The Forest or the Trees? Tackling Simpson’s Paradox with Classification Trees, Production and Operations Management, vol 27 no 4, pp. 696-716.

  5. Shmueli, G. (2017), Research Dilemmas With Behavioral Big Data, Big Data, vol 5 issue 2, pp. 98-119.

  6. Chatla, S. and Shmueli, G. (2017), An Extensive Examination of Linear Regression Models with a Binary Outcome Variable, Journal of the Association for Information Systems (JAIS), vol 18 no 4, article 1.

  7. Yahav, I., Shmueli, G. and Mani, D. (2016), A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Big Data, MIS Quarterly, vol 40 no 4, pp. 819-848.

  8. 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, vol 62 no 11, pp. 3100-3122.

  9. 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.

  10. 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.

  11. 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.

  12. Shmueli, G. and Koppius, O. (2011) “Predictive Analytics in Information Systems Research”, MIS Quarterly, vol 35 no 3, pp. 553-572.

  13. Shmueli, G. (2010), “To Explain or To Predict?”, Statistical Science, vol 25(3), pp. 289-310.

  14. Bapna, R., Jank, W. and Shmueli, G., (2008) “Consumer Surplus in Online Auctions”, Information Systems Research, vol. 19(4), pp. 400 - 416.

  15. 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

Recent Awards

  • 2020 Outstanding Teaching Award, National Tsing Hua University, Taiwan

  • 2020 Elected Fellow, Institute of Mathematical Statistics (IMS)

  • 2019 Outstanding Mentor Award, College of Technology Management, National Tsing Hua University, Taiwan

  • 2018 Outstanding Teaching Award, College of Technology Management, National Tsing Hua University, Taiwan

  • 2016 Outstanding Research Award, Ministry of Science and Technology (MoST), Taiwan

  • 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)