Erick Delage is an associate professor at HEC Montréal in the department of Decision Sciences. He graduated in 2009 with a Ph.D. in Electrical Engineering from Stanford University. During his stay at Stanford, he had the opportunity to work with Professor Andrew Y. Ng, Professor Shie Mannor, and Professor Yinyu Ye. His thesis presented new optimization models for taking into account parameter and distribution uncertainty in a range of decision problems where the knowledge of some parameters is limited to historical samples.

 

Since he joined HEC Montréal, he has entertained a strong interest for quantitative methodologies that can help manage the risks related to market, environmental or physical uncertainty that is present in industrial and financial decision problems. Specifically, his research interests span the areas of optimization, decision analysis, artificial intelligence and applied statistics. He is especially fascinated about how concept of robust optimization can successfully reconcile the design of a decision model with the prevailing ambiguity about outcomes and about how these might be perceived by the decision maker. Applications that have caught his attention include, but are not limited to, portfolio selection, e-commerce, resource allocation, network routing, inventory management and energy production problems.