Spyros Zoumpoulis is an assistant professor of Decision Sciences at INSEAD. His research is on using analytics to optimize decision making, with applications in marketing, healthcare, and revenue management. His current focus is on investigating how to design, and use data from, experiments in order to make optimal personalized decisions, as well as how to evaluate policies that make personalized decisions, such as targeting decisions in marketing and personalized treatment decisions in healthcare.

More generally, he is broadly interested in problems at the interface of learning with data and decision making. His research has appeared in leading management science academic journals such as Management Science and Operations Research.

Spyros has worked with companies including Microsoft, LinkedIn, IBM, Oracle, and Accenture and serves on the advisory board of start-ups in the areas of his expertise. At INSEAD, he teaches the MBA core course on uncertainty, data and judgment, the MBA electives on data science for business and decision models, the MBA business foundations course on quantitative methods, the PhD courses on probability and statistics, and the INSEAD-Sorbonne business foundations course on uncertainty, data and judgment. He has won the Dean's Commendation for Excellence in MBA Teaching award numerous times and has been nominated for the best MBA elective professor award.

Spyros received the B.S., M.Eng., and Ph.D. degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology.

Research

Working papers

Journal publications

Media (selected)

Conference proceedings

  • A. Alban, S. E. Chick, S. I. Zoumpoulis, Expected Value of Information Methods for Contextual Ranking and Selection: Clinical Trials and Simulation Optimization. Proceedings of the 2021 Winter Simulation Conference.
  • I. Kash, P. Key, S. I. Zoumpoulis, Optimal pricing and introduction timing of new virtual machines. Proceedings of the 2018 ACM Conference on Economics and Computation, 26% acceptance
  • M. A. Dahleh, J. N. Tsitsiklis, S. I. Zoumpoulis, The value of temporal data for learning of influence networks: a characterization via Kullback-Leibler divergence, Proceedings of the 54th IEEE Conference on Decision and Control, Osaka, Japan, December 2015
  • M. A. Dahleh, J. N. Tsitsiklis, S. I. Zoumpoulis, The value of temporally richer data for learning of influence networks, Book chapter in Web and Internet Economics, Lecture Notes in Computer Science Volume 8877, pp. 322-323, Proceedings of the 10th Conference on Web and Internet Economics, 30% acceptance, 2014
  • M. A. Dahleh, A. Tahbaz-Salehi, J. N. Tsitsiklis, S. I. Zoumpoulis, Coordination with local information, ACM Performance Evaluation Review, Proceedings of the joint Workshop on Pricing and Incentives in Networks and Systems (W-PIN + NetEcon within ACM Sigmetrics), 30% acceptance, 2013
  • M. A. Dahleh, A. Tahbaz-Salehi, J. N. Tsitsiklis, S. I. Zoumpoulis, On global games of regime change in networks, Proceedings of the 6th Workshop on the Economics of Networks, Systems, and Computation (NetEcon), within 12th ACM Conference on Electronic Commerce, 35% acceptance, 2011
  • O. Patrick Kreidl, J. N. Tsitsiklis, S. I. Zoumpoulis, Decentralized detection in network sensor architectures with feedback, Proceedings of the 48th Annual Allerton Conference on Communications, Control and Computing, 2010

Theses

Contact

Email: [email protected]

Phone: +33 (0)1 60 72 43 26

Campus: Fontainebleau

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