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Subject to: Francesca Maggioni

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Manage episode 373176954 series 3000652
Content provided by Anand Subramanian. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anand Subramanian or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Francesca Maggioni is Associate Professor of Operations Research at the Department of Management, Information and Production Engineering (DIGIP) of the University of Bergamo (Italy). Her research interests concern both methodological and applicative aspects of optimization under uncertainty. From a methodological point of view, she has developed different types of bounds and approximations for stochastic, robust and distributionally robust multistage optimization problems. She applies these methods to solve problems in logistics, transportation, energy production, pension funds and machine learning. On these topics she has published more than 60 scientific articles featured in peer-reviewed operations research and optimization journal like, among others, SIAM Journal on Optimization (SIOPT), European Journal of Operational Research (EJOR), Transportation Science, Journal of Optimization, Theory and Applications (JOTA). She is currently serving the “EURO Working Group on Stochastic Optimization” and the “AIRO Thematic Section of Stochastic Programming” as chair and has served the “Stochastic Programming Society” in the period 2016-2023. She is Associate Editor of the journals “Computational Management Science” (CMS), “EURO Journal on Computational Optimization” (EJCO), “An Official Journal of the Spanish Society of Statistics and Operations Research” (TOP), “Networks” and “International Transactions in Operational Research” (ITOR). She is principal investigator of the PRIN 2020 project "Urban Logistics and sustainable TRAnsportation: OPtimization under uncertainTY and MAchine Learning (ULTRAOPTYMAL) funded by the Italian University and Research Ministry.

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100 episodes

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Manage episode 373176954 series 3000652
Content provided by Anand Subramanian. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anand Subramanian or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Francesca Maggioni is Associate Professor of Operations Research at the Department of Management, Information and Production Engineering (DIGIP) of the University of Bergamo (Italy). Her research interests concern both methodological and applicative aspects of optimization under uncertainty. From a methodological point of view, she has developed different types of bounds and approximations for stochastic, robust and distributionally robust multistage optimization problems. She applies these methods to solve problems in logistics, transportation, energy production, pension funds and machine learning. On these topics she has published more than 60 scientific articles featured in peer-reviewed operations research and optimization journal like, among others, SIAM Journal on Optimization (SIOPT), European Journal of Operational Research (EJOR), Transportation Science, Journal of Optimization, Theory and Applications (JOTA). She is currently serving the “EURO Working Group on Stochastic Optimization” and the “AIRO Thematic Section of Stochastic Programming” as chair and has served the “Stochastic Programming Society” in the period 2016-2023. She is Associate Editor of the journals “Computational Management Science” (CMS), “EURO Journal on Computational Optimization” (EJCO), “An Official Journal of the Spanish Society of Statistics and Operations Research” (TOP), “Networks” and “International Transactions in Operational Research” (ITOR). She is principal investigator of the PRIN 2020 project "Urban Logistics and sustainable TRAnsportation: OPtimization under uncertainTY and MAchine Learning (ULTRAOPTYMAL) funded by the Italian University and Research Ministry.

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100 episodes

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