Ezra's Round Table / Systems Seminar: Stephane Hess (Leeds)
Frank H. T. Rhodes Hall 253
Choice modelling (VS) AND machine learning
Travel demand modelling has traditionally relied on econometric techniques, often structures belonging to the family of (discrete) choice models. In recent years, there has been growing interest in the use of machine learning techniques as an alternative. Much of this work has focussed on contrasting the methods rather than looking at finding synergies. This presentation makes the case for a different approach going forward, looking at using both types of approaches alongside each other, and to pave the way for new methods bringing together the benefits of different disciplines. Four separate case studies are presented, going from work comparing different model families to efforts to integrate them.
Stephane Hess is an internationally recognised expert in the data-driven study and mathematical-modelling of human choice behavior. He has made contributions to the state of the art in the specification, estimation and interpretation of such models, as well as in facilitating the transition of ideas and approaches across disciplines, notably by also working in mathematical psychology and behavioural economics. Although a majority of his applied work has been conducted in the field of transport, he is also very active in health and environmental economics. Together with David Palma, he is the author of Apollo, a highly flexible and powerful free tool for estimating and applying choice models. He is Professor of Choice Modelling and Director of the Choice Modelling Centre at the University of Leeds, where he is based in the Institute for Transport Studies. He is also a part-time professor of decision modelling, artificial intelligence (AI) and mobility research at Delft University of Technology. He is Honorary Professor in choice modelling in the Institute for Transport and Logistics Studies at the University of Sydney and Honorary Professor of modelling behavior in Africa at the University of Cape Town.