Professor Richards, a distinguished scholar with affiliations to MILA, Google DeepMind, and a D.Phil. graduate from Oxford University, has profoundly impacted the field of Computational Neuroscience through the use of Artificial Intelligence.
His illustrious career brims with pioneering advancements and pivotal contributions to the field of neuroscience and the AI industry.
Miguel is a prominent figure in Operational Research, currently serving as the Chair of Operational Research at the University of Edinburgh. With extensive involvement in esteemed organizations like EUROPT and INFORMS, he focuses his research on using mathematical optimization to address complex, large-scale problems.
Notably, Miguel has made significant contributions to the development of smart grids, combining traditional power systems with bidirectional information and energy flows between suppliers and consumers.
Loubna is a Research Chair Professor of Artificial Intelligence for Supply chain management at Université du Québec à Rimouski (UQAR). Her research focuses on the development and application of machine learning and operations research approaches to data-driven decision-making.
She contributes to reforming the management and digitalization of industrial processes, working across industries and applying her techniques to sustainable supply chains, climate change risk mitigation, optimization, and more.
Loubna is an active member of the community, participating in industry research projects, heading committees, and publishing articles in international journals.
As a strategic tech leader and innovator, Lalit specializes in driving digital transformation for Fortune 500 companies.
With a track record of successfully leading transformative projects across diverse industries, he has built customer-focused development teams that facilitate seamless innovation and propel organizations towards their goals.
With nearly two decades of global experience as a principal consultant, Max has made significant contributions to the growth of multiple technology companies.
As a former strategy consultant he advised Fortune 500 companies. Additionally, he successfully built and scaled technology organizations, which achieved a remarkable IPO within a span of a few years.
Okan Arslan is a distinguished scholar in operations research and transportation science, with a Ph.D. from Bilkent University in Industrial Engineering.
Currently an Assistant Professor at the Department of Decision Sciences at HEC Montréal, Canada, his research, spanning from large networks to last-mile delivery systems, has garnered him accolades such as the Prix Nouveau Chercheur and the Best Application Paper Award.
Okan recently showcased his expertise by securing one of the top spots in Amazon’s Global Last Mile Routing Research Challenge, a collaboration between the online retail behemoth and the Massachusetts Institute of Technology (MIT).
Michel Gendreau is a prominent figure in the fields of applied mathematics, operations research, and optimization.
He currently holds the position of Professor in the Department of Mathematics and Industrial Engineering at École Polytechnique de Montréal and is also an Adjunct Professor in the Department of Computer Science and Operations Research at the University of Montreal. Throughout his career, he has held key roles in renowned research institutions, including serving as Director of the Transportation Research Center at the University of Montreal and Director at CIRRELT(Interuniversity Research Centre on Enterprise Networks, Logistics, and Transportation).
These roles underscore his leadership in developing innovative approaches to complex challenges in logistics, networks, and industrial systems.
Since beginning his career in 1984, Michel Gendreau has produced a remarkable body of scientific work, with over 400 articles published in leading scientific journals and conferences. This impressive output reflects his ability to innovate in critical areas such as energy system optimization and the mathematical modeling of complex industrial processes.
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