Inside Our ProgramProgram Events
Events
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Oct8
EVENT DETAILS
Abstract: Flexibility is a cornerstone of operations management, crucial to hedge stochasticity in product demands, service requirements, and resource allocation. In two-sided platforms, flexibility is also two-sided and can be viewed as the compatibility of agents on one side with agents on the other side. Platform actions often influence the flexibility on either the demand or the supply side. But how should flexibility be jointly allocated across different sides? Whereas the literature has traditionally focused on only one side at a time, our work initiates the study of two-sided flexibility in matching platforms. We propose a parsimonious matching model in random graphs and identify the flexibility allocation that optimizes the expected size of a maximum matching. Our findings reveal that flexibility allocation is a first-order issue: for a given flexibility budget, the resulting matching size can vary greatly depending on how the budget is allocated. Moreover, even in the simple and symmetric settings we study, the quest for the optimal allocation is complicated. In particular, easy and costly mistakes can be made if the flexibility decisions on the demand and supply side are optimized independently (e.g., by two different teams in the company), rather than jointly. To guide the search for optimal flexibility allocation, we uncover two effects -- flexibility cannibalization and flexibility asymmetry -- that govern when the optimal design places the flexibility budget only on one side or equally on both sides. In doing so we identify the study of two-sided flexibility as a significant aspect of platform efficiency.
Bio: Sébastien Martin is an assistant professor of operations at the Kellogg School of Management, Northwestern University. He received his M.Sc. in applied math from Ecole polytechnique (France) in 2015 and his Ph.D. in operations research from MIT in 2019. His research focuses on designing large-scale optimization algorithms for public sector operations and online platforms. His work has been recognized with two Franz Edelman Laureate Awards and the Dantzig Best Thesis Award. He designed Lyft's dispatch algorithm, optimized the school transportation systems of Boston and San Francisco, and created Kellogg's first AI teaching assistant.
TIME Tuesday, October 8, 2024 at 11:00 AM - 12:00 PM
LOCATION Hive Annex, Ford Motor Company Engineering Design Center map it
CONTACT Kendall Minta kendall.minta@gmail.com EMAIL
CALENDAR Department of Industrial Engineering and Management Sciences (IEMS)
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Nov15
EVENT DETAILS
Join us for an insightful seminar featuring Sergey Shebalov about the resurgence of Artificial Intelligence. We will delve into real-world use cases, the challenges and opportunities in AI adoption, and the impact of AI on the travel industry.
Lecture Summary: Artificial Intelligence is experiencing resurrection over the last several years. The number of use cases already implemented in practice and the amount of investment allocated to development and adoption of this technology indicates that this time it's here to stay. While several challenges still remain and some new ones are anticipated the path towards Al becoming as common as computer, smartphone or internet is clear. We will discuss this journey on the example of the travel industry. We'll consider several main applications of Al that already provided significant benefits, a typical process these applications go through from an idea to a full-scale adoption, and the skills required to support that process from the new generation of leaders, scientists, engineers and practitioners.
Sergey Shebalov is a VP of Data Science and Head of Research at Sabre. He leads the Sabre Labs team responsible for development and implementation of complex Al decision support systems. Sergey holds PhD in mathematics from University of Illinois and has two decades of experience in the travel industry IT. His area of expertise is intelligent retailing,
resource optimization and adoption of Al in practice.
Location: Krebs Classroom, McCormick Education Center, 2311 Campus Dr
TIME Friday, November 15, 2024 at 3:30 PM - 4:30 PM
LOCATION Krebs Classroom, Henry Crown Sports Pavilion map it
CONTACT Master of Science in Machine Learning and Data Science Program mlds@northwestern.edu EMAIL
CALENDAR Master of Science in Machine Learning and Data Science (MLDS)
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Dec7
EVENT DETAILS
Fall classes end
TIME Saturday, December 7, 2024
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Dec14
EVENT DETAILS
The ceremony will take place on Saturday, December 14 in Pick-Staiger Concert Hall, 50 Arts Circle Drive.
*No tickets required
TIME Saturday, December 14, 2024 at 4:00 PM - 6:00 PM
LOCATION Pick-Staiger Concert Hall map it
CONTACT Andi Joppie andi.joppie@northwestern.edu EMAIL
CALENDAR McCormick School of Engineering and Applied Science