Recent Machine Learning and Data Science Applications in Transportation and Logistics

Abstract:
This presentation will explore the current state-of-the-art methodologies in machine learning and statistics that are employed in various application areas from transportation and logistics, including arrival time prediction, demand forecasting, industrial processes optimization, the vehicle routing problem and anomaly detection. This talk, with its primary focus on arrival time prediction and demand forecasting, will categorize the related work according to various machine learning methodologies so as to present the methods’ evolution over time, their combinations and their connection with the various applications in the specified fields. Finally, some future directions and possibilities will be discussed.

About the Speaker:
Dr. Samrat Roy is a faculty member at IIM Ahmedabad in the Operations and Decision Sciences Area. Prior to this position, he worked as a postdoctoral researcher at the Wharton School (Department of Statistics and Data Science) in the University of Pennsylvania. He completed his M.STAT. from Indian Statistical Institute and received his Ph.D. in Statistics from the University of Florida (UF). Before starting his journey as a doctoral student at the UF, he worked at Ernst & Young and Credit Suisse as a credit risk model developer. His research includes High-dimensional Statistics, Tensor Models, Causal Inference, Observational Studies and Time Series Models.