How to build an effective analytics practice
From designing intelligent decision processes to tapping the full power of deep learning, here are data practices to adopt now from MIT Sloan analytics faculty.
Faculty
Alexandre Jacquillat is the 1942 Career Development Professor and an Associate Professor of Operations Research and Statistics at the MIT Sloan School of Management.
His research focuses on data-driven decision-making, spanning stochastic optimization, integer optimization, and machine learning. In particular, his research aims to develop scalable algorithms and decision-making tools to support more efficient, equitable, and sustainable operations in transportation and logistics—with a particular interest in air traffic management, on-demand microtransit in urban mobility, and collaborative logistics.
Alexandre is the recipient of several research awards, including the Best Paper Award from the INFORMS Transportation Science and Logistics Society (2017, 2021), the George B. Dantzig Dissertation Award from INFORMS (2015), the Best Dissertation Award from the INFORMS Transportation and Logistics Society (2015), and the L.E. Rivot Medal from the French Academy of Science. He was named in the list of Leading Academic Data Leaders from the Chief Data Officer Magazine in 2021 and 2022.
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 holds 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.
Featured Publication
"Routing Optimization with Vehicle-Customer Coordination."Zhang, Wei, Alexandre Jacquillat, Kai Wang, and Shuaian Wang. Management Science. Forthcoming. SSRN Preprint.
Featured Publication
"Vertiport Planning for Urban Aerial Mobility: An Adaptive Discretization Approach."Wang, Kai, Alexandre Jacquillat, and Vikrant Vaze. Manufacturing and Service Operations Management. Forthcoming. Supplemental Materials.
Wang, Kai, and Alexandre Jacquillat. Operations Research. Forthcoming.
Cohen, Maxime, Alexandre Jacquillat, and Juan Camilo Serpa. Management Science. Forthcoming.
Birolini, Sebastian, Alexandre Jacquilat, Phillip Schmedeman, and Nuno Ribeiro. Transportation Science Vol. 57, No. 1 (2023): 4-26. Supplemental Materials.
Cohen, Maxime, Alexandre Jacquillat, and Haotian Song. Manufacturing and Service Operations Management Vol. 25, No. 1 (2023): 148-167. SSRN Preprint. Supplemental Materials.
From designing intelligent decision processes to tapping the full power of deep learning, here are data practices to adopt now from MIT Sloan analytics faculty.
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