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ניווט מהיר:

מידע כללי

Tomer Geva is a tenured senior lecturer at Tel-Aviv University and faculty member in the Information Systems department. Tomer was the founder of the Business Data Science program at Tel-Aviv University and was the head of this program between 2015 and 2021.

Tomer’s research interests focus on developing Machine Learning-based methods for solving business problems, with specific interests in using large-scale online data for business decision making, and developing Machine Learning and AI methods to improve and assess workers’ decisions in crowdsourcing and organizational environments.

Tomer currently serves as a Senior Editor for Decision Support Systems (DSS) journal and had previously served as an Associate Editor for "Big Data" and "Decision Sciences" journals. Tomer's research was published in both Management Journals and Data Science Journals including: MIS Quarterly (MISQ), Information Systems Research (ISR), Production and Operations Management (POMS), Decision Support Systems, IEEE TKDE, and Data Mining and Knowledge Discovery. His work also benefited from generous funding from different foundations and companies including: Israel Science Foundation (ISF), Marketing Science Institute (MSI), and Google.

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.

פרסומים

  • Geva, Tomer, and Maytal Saar‐Tsechansky. "Who Is a Better Decision Maker? Data‐Driven Expert Ranking Under Unobserved Quality." Production and Operations Management 30, no. 1 (2021): 127-144.
     
  • “Data-Driven Link Screening for Increasing Network Predictability.” Tomer Geva and Inbal Yahav”. IEEE Transactions on Knowledge and Data Engineering. 33(6): 2380 – 2391. (2021).
     
  • 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. (2016).
     
  • 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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