Spyros Zoumpoulis

Spyros Zoumpoulis is an assistant professor of Decision Sciences at INSEAD. His research is on using analytics and machine learning to optimize marketing and operations decisions. His current focus is on investigating how to use data from field experiments to make optimal decisions, such as targeting decisions in marketing. More generally, he is broadly interested in problems at the interface of networks, learning with data, and decision making. His research has appeared in leading management 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 big data analytics and models for strategic planning, 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 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.

PUBLICATIONS

• WORKING PAPERS - Efficiently Evaluating Targeting Policies Using Field Experiments
• WORKING PAPERS - Using Past Responders to Target Non-Responders
• JOURNAL ARTICLES - Technical Note-Coordination with Local Information - Operations Research
• JOURNAL ARTICLES - The Value of Field Experiments - Management Science
• JOURNAL ARTICLES - Right-Protected Data Publishing with Provable Distance-based Mining - IEEE Transactions on Knowledge and Data Engineering
• JOURNAL ARTICLES - On Decentralized Detection With Partial Information Sharing Among Sensors - IEEE Transactions on Signal Processing

RESEARCH AREAS

Analytics for optimal decisions in marketing and operations, efficient learning with data, field experiments., Networks, Learning with Data, Field Experiments in Marketing, Influence, Data Mining, Coordination using Game-theoretic Modeling

TEACHING AREAS

Uncertainty, Data and Judgment (MBA), Data Science for Business (MBA), Decision Models (MBA), Quantitative Methods (MBA), Probability and Statistics (PhD), Uncertainty, Data and Judgment (INSEAD-Sorbonne business foundations), Models for Strategic Planning