Seminar - Predictive Models for Operations Management
Abstract: In this talk, we discuss the application of machine learning models to support decision-making in three operational contexts. First, we develop a model for real-time interval prediction of waiting times for examinations. Second, we compare models for predicting demand for infusion therapy as a consequence of modifications in providers’ scheduling. Third, we propose a methodology for explaining inconsistencies in repeated waiting time predictions. The first two projects are applied in nature and conducted in collaboration with a large cancer hospital, while the third project is methodological and motivated by concrete applications.
These projects were conducted jointly with Dawn He, Yashi Huang, and Arik Senderovich.
Bio: Yaron Shaposhnik is an Associate Professor of Operations Management and Information Systems at the Simon Business School in the University of Rochester. Most broadly, he is interested in the optimization and analysis of mathematical models that capture real world problems, and in developing decision support tools that leverage analytics to improve operations.
