Srikanth Jagabathula, an assistant professor in the Information, Operations, & Management Sciences department at the New York University Stern School of Business was recently recognized by the National Science Foundation (NSF) with its Faculty Early Career Development Award (CAREER). As part of this award, Jagabathula will receive a total of $500,000 over the next five years to further his research in developing data-driven modeling and learning techniques with the goal of improving the accuracy of operational decision making.
“We are proud of professor Jagabathula’s research and the recognition it has received from the National Science Foundation,” Peter Henry, dean of NYU Stern was quoted saying in a university press release.
Jagabathula’s research is expected to lead to easy-to-use techniques for a wide range of managerial decisions: the right products to design, the right products and prices to offer to customers, and the right quantity of each product to carry.
Traditional approaches have focused either on selecting an appropriate model and fitting it to the data or on efficiently solving a decision problem when given the model, leaving the model selection itself to an expert. Neither approach scales to current retail applications, which are characterized by diverse demand patterns, products, and types of data.
Jagabathula’s research will instead blend techniques from machine learning, statistics, and operations to design an approach that starts with a type of data (purchase transactions, click-streams, marketing studies, choice of insurance policies, etc.) and ends with an operational decision.