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DTSTART:19700329T020000
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DTSTART:19701025T030000
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DTSTAMP:20250520T145414
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SUMMARY:Talk of Prof. Andrea Simonetto
DESCRIPTION:Abstract\nCan we allow humans to pick among different, yet reasonably similar, decisions? Are we able to\nconstruct optimization problems whose outcomes are sets of feasible, close-to-optimal decisions for\nhuman users to pick from, instead of a single, hardly explainable, do-as-I-say “optimal”\ndirective?\nIn this seminar, we explore two complementary ways to render optimization problems stemming from\ncyber-physical applications flexible. In doing so, the optimization outcome is a trade-off between\nengineering best and flexibility for the users to decide to do something slightly different. The\nfirst method is based on robust optimization and convex reformulations. The second method is\nstochastic and inspired by stochastic optimization with decision-dependent distributions. Biographical Information\nAndrea Simonetto obtained his PhD degree in system and control at Delft University of\nTechnology, the Netherlands, in 2012. He then spent 3+1 years as a Post-Doctoral researcher. First\nwith the Circuits and Systems Group at Delft University of Technology, and then, with the ICTEAM\nInstitute at UCLouvain, Belgium. Subsequently, from February 2017 to August 2021, Andrea was a\nresearch staff member with the optimization and control group, then the AI and Quantum group at IBM\nResearch Ireland. And, finally, in September 2021, Andrea became a research professor at ENSTA\nParis, Institut Polytechnique de Paris.\n\n\n\n\n  
DTSTART;TZID=Europe/Berlin:20250527T160000
DTEND;TZID=Europe/Berlin:19700101T010000
LOCATION:Institute for Systems Theory and Automatic Control, , Seminar room 2.255, Pfaffenwaldring 9, 70569  Stuttgart, Campus Vaihingen 
URL;VALUE=URI:https://www.ist.uni-stuttgart.de/events/Talk-of-Prof.-Andrea-Simonetto/
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