Dr. Tomer Geva

Coller School of Management
הפקולטה לניהול ע"ש קולר סגל אקדמי בכיר

Short Biography

Tomer Geva is a (tenured) senior lecturer at Tel-Aviv University and the head of the Business Analytics Program at Tel-Aviv University’s School of Management. Tomer founded this program in 2015.

Tomer Geva’s research interests include developing Data Science methods for solving business problems, with specific interests in using large-scale online data for business decision making, and using machine learning and AI methods to manage workers in crowdsourcing and organizational environments.

Tomer’s research was published in various journals such as MIS Quarterly, Information Systems Research, Data Mining and Knowledge Discovery, IEEE TKDE, and Decision Support Systems, as well as conference proceedings such as ICIS. His work also benefited from generous funding by different foundations and companies including Israel Science Foundation (ISF), Marketing Science Institute (MSI), and Google. Tomer serves as an Associate Editor “Decision Sciences” journal and previously served as an Associate Editor for “Big-Data” journal.

Before joining Tel-Aviv University Tomer was a visiting scholar at NYU Stern School of Business and a post-doctoral research scientist at Google. Prior to his Ph.D. studies, he held various engineering and management positions in the high-tech industry.

Selected Publications

  • Geva, Tomer, and Inbal Yahav. "Data-Driven Link Screening for Increasing Network Predictability." IEEE Transactions on Knowledge and Data Engineering (Forthcoming).
  • Geva, Tomer, Maytal Saar-Tsechansky, and Harel Lustiger. "More for less: adaptive labeling payments in online labor markets." Data Mining and Knowledge Discovery 33, no. 6 (2019): 1625-1673.
  • Geva, Tomer, Gal Oestreicher-Singer, Niv Efron, and Yair Shimshoni. "Using forum and search data for sales prediction of high-involvement products." MIS Quarterly 41 (1), 65-82 (2017).
  • Brynjolfsson, Erik, Tomer Geva, and Shachar Reichman. "Crowd-squared: amplifying the predictive power of search trend data." MIS Quarterly 40 (4), 941-961. (2019).
  • Dhar, Vasant, Tomer Geva, Gal Oestreicher-Singer, and Arun Sundararajan. "Prediction in economic networks." Information Systems Research 25, no. 2 (2014): 264-284.
  • Geva, Tomer, and Jacob Zahavi. "Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news." Decision Support Systems 57 (2014): 212-223.
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