Omar Besbes
- Vikram S. Pandit Professor of Business
- Decision, Risk, and Operations Division
- Areas of Expertise
- Artificial Intelligence (AI), Marketplace Design, Operations & Supply Chain Management
- Contact
- Office: 982 Kravis
- E-mail: [email protected]
- Links
- Curriculum Vitae
Omar Besbes's primary research interests are in the area of data-driven decision-making with a focus on applications in e-commerce, pricing and revenue management, online advertising, operations management and general service systems. His research has been recognized by multiple prizes, including the 2019 Frederick W. Lanchester Prize, the 2017 M&SOM society Young Scholar Prize, the 2013 M&SOM best paper award and the 2012 INFORMS Revenue Management and Pricing Section prize. He serves on the editorial boards of Management Science and Operations Research.
He has taught core MBA courses in Operations Management and Business Analytics, an MBA elective on advanced Business Analytics, as well as various Ph.D. seminars on stochastic models, revenue management and data-driven decision-making. He is a recipient of the Dean's award for teaching excellence in the core at Columbia Business School.
Omar is a graduate of Ecole Polytechnique (France) and received a M.Sc. from Stanford University in 2000 and a Ph.D. from Columbia University in 2008. Before joining Columbia, he was on the faculty at the Wharton School, University of Pennsylvania.
- Education
-
Ingenieur de l'Ecole, Polytechnique, France, 1999; MSc, Stanford University, 2000; PhD, Columbia University, 2008
- Joined CBS
- 2009
All Activities
Using AI in the Classroom at Columbia Business School
Three Key Insights on the Future of Prediction
Refining and Rethinking Digital Decision-Making
Columbia Business School Expands Digital Future Initiative
The Intersection of Data & Human Experience
DRO PhD students accept faculty positions at UCLA, UNC, and Imperial College London
School Welcomes New Faculty Members
- Case ID
- 250201
Connecting the Dots for NYC Clean Power: The Case of NineDot Energy
What are the logistical challenges inherent in a company’s clean energy business model, using analytical techniques?
- Case ID
- 210211
At the Frontier of Retail in the 21st Century: Modern Fulfillment and The Case of FlexiWeight
With a goal to revolutionize the way America exercises, can Flexiweight find the right fulfillment model to deliver on its mission?
- Case ID
- 210210
Continuous Quality Monitoring via Data and Analytics at Patina Beauty
How should Patina Beauty's analytics team respond to a spike in online complaints from its Chinese customers?
- Case ID
- 210204
Music Streaming
Would the listener base for music streaming services continue to grow—and would services be able to differentiate themselves in this increasingly competitive industry?
- Case ID
- 140204
DSS
- Case ID
- 140206
Tahoe Healthcare Systems
Has Tahoe Healthcare's CareTracker system effectively—and cost efficiently—reduced the readmission rate in its pilot program?
- Case ID
- 140205
H&K
- Case ID
- 140202
Pandora Internet Radio
- Case ID
- 110206SPA
Beleza Natural (Spanish Translation)
How should the management of a highly successful chain of beauty institutes respond to operational challenges in the face of rapid growth?
- Case ID
- 140201
Nomis Solutions (A and B)
How will a startup company planning to offer pricing-optimization solutions to financial service firms persuade potential clients to use their products and services?
- Case ID
- 112105
Lean Operations: From Efficiency to Profit
What are the potential implications of broadly implementing the Toyota Production System for GM's production strategy and profitability?
- Case ID
- 110206
Beleza Natural
How should the management of a highly successful chain of beauty institutes respond to operational challenges in the face of rapid growth?
- Case ID
- 110204
Emergency Department Congestion at Saintemarie University Hospital
How should the CEO of a major metropolitan hospital address congestion and prolonged wait times in the emergency department?