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SUMMARY:Machine Learning and Optimization for Enhanced Decision-Making Und
 er Uncertainty
DTSTART:20250501T171500
DTEND:20250501T181500
DTSTAMP:20260501T071026Z
UID:5f6ae3e35e56e1979f05037f3647ea418002ebcca2b5624a796b7bb1
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Emma Frejinger\nAbstract\nDecision makers across variou
 s domains often face problems that are subject to uncertainty. Consider pl
 anning transport services\, operating power systems\, determining infrastr
 ucture locations\, and setting pricing strategies. The integration of mach
 ine learning and optimization methods has gained significant attention\, b
 oth for accelerating solution methods and for enhancing models by training
  machine learning algorithms on task-specific losses rather than conventio
 nal prediction losses.\n\nWe provide a brief overview of this literature a
 nd highlight key challenges\, notably decision-dependent uncertainty which
  remains particularly difficult to address. To illustrate\, we examine the
  competitive facility location problem and introduce a methodology for han
 dling decision-dependent demand uncertainty without imposing strong distri
 butional assumptions. Furthermore\, we position the topic within the broad
 er area of contextual stochastic optimization and outline future research 
 directions in integrated learning and optimization that hold practical rel
 evance.\n\nShort bio\nEmma Frejinger is a professor in the Department of C
 omputer Science and Operations Research at Université de Montréal where 
 she holds a Canada Research Chair and an industrial chair funded by the Ca
 nadian National Railway Company. Her research is application-driven and fo
 cuses on innovative combinations of methodologies from machine learning an
 d operations research to solve large-scale decision-making problems.\n\nEm
 ma has extensive experience leading collaborative research projects and wo
 rking with industry\, predominantly within the transportation sector. She 
 serves as a scientific advisor for IVADO Labs\, an AI solution provider\; 
 as an academic affiliate with Analysis Group\; and as an associate member 
 of the machine learning institute Mila. Before joining Université de Mont
 réal in 2013\, Emma was a faculty member at KTH Royal Institute of Techno
 logy in Sweden. She holds a Ph.D. in mathematics from EPFL.\n 
LOCATION:CM 1 4 https://plan.epfl.ch/?room==CM%201%204 https://epfl.zoom.u
 s/j/62822431194
STATUS:CONFIRMED
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