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X-WR-CALNAME:cmc.deusto.eus
X-WR-CALDESC:DeustoCCM - Chair of Computational Mathematics at University of Deusto
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UID:MEC-56b68074a594752f33faa659f227ac65@cmc.deusto.eus
DTSTART:20240515T120000Z
DTEND:20240515T140000Z
DTSTAMP:20251031T212800Z
CREATED:20251031
LAST-MODIFIED:20251031
PRIORITY:5
TRANSP:OPAQUE
SUMMARY:FAU MoD Lecture: Using system knowledge for improved sample efficiency in data-driven modeling and control of complex technical systems
DESCRIPTION:Date: Wed. May 15, 2024\nEvent: FAU MoD Lecture\nOrganized by: FAU MoD, the Research Center for Mathematics of Data at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)\nFAU MoD Lecture: Using system knowledge for improved sample efficiency in data-driven modeling and control of complex technical systems\nSpeaker: Prof. Dr. Sebastian Peitz\nAffiliation: Universität Paderborn (Germany)\nAbstract.  Modern technical systems such as autonomous vehicles, the electric grid or nuclear fusion reactors are extremely complex, which requires powerful techniques for predicting or controlling their behavior. As in almost all areas of science as well as our daily lives, machine learning has had a huge impact on the area of modeling and control of technical systems in recent years. However, the complexity of these systems renders the learning very data-hungry. The aim of this talk is thus to discuss different approaches to leverage system knowledge – and in particular symmetries – such that we can significantly improve the sample efficiency. Our discussion ranges from learning the dynamics from data to reinforcement learning. We will emphasize the benefits of exploiting knowledge using various examples from fluid mechanics.\n\nSee poster\nBIO.- Sebastian Peitz received his B.Sc. and M.Sc. degrees in mechanical engineering from RWTH Aachen University, Germany, in 2011 and 2013, respectively, and his Ph.D. in Mathematics from Paderborn University in 2017. He is currently assistant professor for “Data Science for Engineering” at the Department of Computer Science at Paderborn University. His research interests are multiobjective optimization, optimal control, and data-driven modeling and control of complex systems.\nAUDIENCE\nThis is a hybrid event (On-site/online) open to: Public, Students, Postdocs, Professors, Faculty, Alumni and the scientific community all around the world.\nWHEN\nWed. May 15, 2024 at 14:00H (Berlin time)\nWHERE\nOn-site / Online\n[On-site]\nFriedrich-Alexander-Universität Erlangen-Nürnberg.\nRoom H13 Johann-Radon-Hörsaal\nCauerstraße 11, 91058 Erlangen\nGPS-Koord. Raum: 49.573764N, 11.030028E\n[Online]\nFAU Zoom link\nMeeting ID: 624 1094 3213 | PIN code: 694096\nThis event on: FAU Fak. Nat. | FAU Mathematik |  LinkedIn\n \nYou might like:\n• FAU MoD Lectures\n• FAU MoD Lecture: Image Reconstruction – The Dialectic of Modelling and Learning by Prof. Dr. Martin Burger\n• FAU MoD Lecture: The role of Artificial Intelligence in the future of mathematics by Prof. Dr. Amaury Hayat\n• FAU MoD Lecture: FAU MoD Lecture. Special November 2023 by Prof. Dr. Michael Kohlhase and Prof. Dr. Edriss S. Titi\n• FAU MoD Lecture: Free boundary regularity for the obstacle problem by Prof. Dr. Alessio Figalli\n• FAU MoD Lecture: Physics-Based and Data-Driven-Based Algorithms for the Simulation of the Heart Function  by Prof. Dr. Alfio Quarteroni\n• FAU MoD Lecture: From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus?  by Prof. Dr. George Karniadakis\n• FAU MoD Lecture: From Alan Turing to contact geometry: Towards a “Fluid computer” by Prof. Dr. Eva Miranda\n• FAU MoD Lecture:  Applications of AAA Rational Approximation by Prof. Dr. Nick Trefethen\n• FAU MoD Lecture:  Learning-Based Optimization and PDE Control in User-Assignable Finite Time by Prof. Dr. Miroslav Krstic\n_\nDon’t miss out our last news and connect with us!\nLinkedIn | Twitter | Instagram\n
URL:https://cmc.deusto.eus/events-calendar/fau-mod-lecture-using-system-knowledge-for-improved-sample-efficiency-in-data-driven-modeling-and-control-of-complex-technical-systems/
ORGANIZER;CN=FAU MoD:MAILTO:
CATEGORIES:FAU MoD Lecture,Seminar/Talk
LOCATION:Worldwide
ATTACH;FMTTYPE=image/png:https://cmc.deusto.eus/wp-content/uploads/FAUMoD_lecture_sPeitz_15may2024.png
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