現職 Employment 

• Chair 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 and machine learning methods for data from digital platforms

• Statistical strategy:  empirical modeling for scientific research

• Business analytics

1. Danks, N., Ray, S., and Shmueli, G. (2024), The Composite Overfit Analysis Framework: Assessing the Out-of-sample Generalizability of Construct-based Models Using Predictive Deviance, Deviance Trees, and Unstable Paths, Management Science, vol 70 issue 1, pp. 647-‌669.

2. Shmueli, G., and Tafti, A. (2023), How to “Improve” Prediction Using Behavior Modification, International Journal on Forecasting, vol 39 issue 2, pp. 541-555.

3. Greene, T., Shmueli, G., and Ray, S. (2023), Taking the Person Seriously: Ethically-aware IS Research in the Era of Reinforcement Learning-based Personalization, Journal of the Association for Information Systems (JAIS), 24(6), 1527-1561.

4. Greene, T., Martens, D., and Shmueli, G. (2022), Barriers to Academic Data Science Research in the New Realm of Algorithmic Behaviour Modification by Digital Platforms, Nature Machine Intelligence, issue 4, pp. 323–330.

5. Tafti, A. R. and Shmueli, G. (2020), "Beyond overall treatment effects: Leveraging covariates in randomized experiments guided by causal structure", Information Systems Research, vol 31 issue 4, pp. 1183-1199. 

6. 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. 

7. 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. 

8. 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. 

9. 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. 

10. 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. 

11. 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.

12. 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.

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

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

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