Daniela Saban

Research Statement

Professor Saban's research interests lie in the interface of operations, economics and computer science. Much of her current research focuses on decision-making in competitive environments. In particular, she uses techniques from game theory, applied probability and optimization to study how the strategic interactions between multiple agents can impact firms, governments, and individuals.

Research Interests

• Supply Chain Management
• Procurement Mechanisms
• Resource Allocation
• Market Design

Bio

Daniela Saban is an Assistant Professor of Operations, Information and Technology at Stanford University’s Graduate School of Business. She received her PhD in Operations Management from Columbia Business School in 2015. Professor Saban also holds B.Sc. (2006) and M.Sc. (2009) degrees in Computer Science from University of Buenos Aires.

Academic Degrees

• PhD, Operations Management, Graduate School of Business, Columbia University, 2015
• MS, Computer Science, Universidad de Buenos Aires, 2009
• BS, Computer Science, Universidad de Buenos Aires, 2006

Awards and Honors

• The Paul and Sandra Montrone Doctoral Fellowship, 2014 - 2015
• Columbia University - Glasgow University Exchange Program Fellowship, 2014
• Deming Doctoral Research Fellowship, The W. Edwards Deming Center, 2013
• Doctoral Fellowship, Columbia Business School, 2010 - 2015
• Research Fellowship, Agencia Nacional de Promocion Cientifica y Tecnologica (equivalent to NSF), Argentina, 2009 - 2010
• Tesis de Licenciatura (MSc. Thesis): Finalist in the National Thesis Contest, organized as part of the Jornadas Argentinas de Informatica, 2009

Teaching

Degree Courses

2017-18

OIT 666: Engineering Online Markets

This class will explore topics the intersection of operations, engineering, and economics relevant to modern internet marketplaces, including those for dating, labor, accommodation, services, and rides. The objective of the class is to introduce...

2016-17

OIT 245: Optimization and Simulation Modeling

This course provides basic skills in quantitative modeling. The objective is to familiarize students with the main steps in an analytical approach to business decision making: constructing an abstract model for a relevant business problem,...