Time

1:40pm - 3:00pm

Location

1605 Tilia, Room 1103, West Village

Speaker(s)

Abstract

Ports connect international supply chains and are essential to the global economic and trade system. It is estimated that ports are responsible for facilitating around 90% of the world trade. They must reach high operational efficiency and service levels to yield productivity results while simultaneously facing many difficulties. Global supply chain disruptions have raised many concerns on Ports productivity and sustainability, among which Port’s efficiency, and management of Emissions are main issues to deal with. The goal of this talk is to present how, with the use of a set of machine learning models linked to an optimization framework, we could help Port decision support information systems deliver smarter processes in Ports, to grow support for more sustainable operations. This holistic view of AI-based decision-making enhances decision support capabilities and high performance through advanced analytics, machine learning and a keen ability to implement intelligent self-evolving optimization algorithms.”

Biographical Sketch

Carlos D. Paternina Arboleda served as a professor at Universidad del Norte in Colombia for 27 years and is now teaching and conducting research with the management information systems department at the Fowler College of Business. He currently teaches Introduction to Operations and Supply Chain Management (BA-360) and Operations and Supply Chain Management (BA-644).

Paternina’s research has been published in numerous top engineering, management and logistics journals and he has been honored as an “Outstanding Professor” while at Universidad del Norte. He earned both his Ph.D. and master’s degree in industrial engineering at the University of South Florida. His primary areas of research are supply chain analytics and optimization, transportation and distributions systems.