A new take on the air traffic flow management problem by considering passenger itineraries (as opposed to flight itineraries only), using machine learning and optimization by Dr Alexandre JACQUILLAT (5 June 2020)
Title: A new take on the air traffic flow management problem by considering passenger itineraries (as opposed to flight itineraries only), using machine learning and optimization
Speaker: Dr Alexandre JACQUILLAT, Assistant Professor, Operations Research and Statistics, Sloan School of Management, Massachusetts Institute of Technology
Date: 5 June 2020
Alexandre Jacquillat is an Assistant Professor of Operations Research and Statistics at the MIT Sloan School of Management.
His research focuses on data-driven decision-making, spanning stochastic optimization, large-scale optimization, mechanism design and field experimentation. His primary focus is on problems of scheduling, operations and pricing in the transportation sector—with a particular interest in air traffic management and on-demand mobility.
Alexandre is the recipient of several research awards, including the 2017 Best Paper Award from the INFORMS Transportation Science and Logistics Society, the 2015 George B. Dantzig Dissertation Award from INFORMS, the 2015 Dissertation Award from the INFORMS Transportation and Logistics Society, the Milton Pikarsky Memorial Award from the Council of University Transportation Centers, and the L.E. Rivot Medal from the French Academy of Science.
Prior to joining MIT, Alexandre was an Assistant Professor of Operations Research and Public Policy at Carnegie Mellon University’s Heinz College. Alexandre also worked with McKinsey & Co. and Booz Allen Hamilton, advising leading companies and governmental organizations in transportation analytics. He received a PhD in engineering systems from MIT, a Master of Science in technology and policy from MIT, and a Master of Science in applied mathematics from the École Polytechnique.