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X-ORIGINAL-URL:https://cmc.deusto.eus/
X-WR-CALNAME:cmc.deusto.eus
X-WR-CALDESC:DeustoCCM - Chair of Computational Mathematics at University of Deusto
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CLASS:PUBLIC
UID:MEC-c611c3bb714aa29ef5c4dbee6eb0e8c8@cmc.deusto.eus
DTSTART:20241024T140000Z
DTEND:20241024T153000Z
DTSTAMP:20251031T212700Z
CREATED:20251031
LAST-MODIFIED:20251031
PRIORITY:5
TRANSP:OPAQUE
SUMMARY:FAU MoD Lecture: New avenues for the interaction of computational mechanics and machine learning
DESCRIPTION:Date: Thu. October 24, 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: New avenues for the interaction of computational mechanics and machine learning\nSpeaker: Prof. Dr. Paolo Zunino\nAffiliation: MOX, Politecnico di Milano (Italy)\nAbstract. Neural networks and learning algorithms have gained substantial attention among researchers engaged in computational mechanics. Notably, there are well-established methodologies for employing these tools in solving mathematical models based on partial differential equations. Additionally, a significant overlap exists between the machine learning and computational science and engineering communities in the realm of data-driven reduced order models. After reviewing the main trends in this field, we will discuss novel emerging approaches such as the application of learning algorithms to expedite the resolution of linear systems or to foster the approximation of multiscale problems.\n\nSee poster\nBIO.- Paolo Zunino is Full Professor in Numerical Analysis at the laboratory of Modeling and Scientific Computing (MOX), Department of Mathematics, Politecnico di Milano. His research interests concern the development of numerical methods for partial differential equations, with focus on multiscale and reduced order models applied to life sciences. He is particularly interested in coupled problems involving lower dimensional manifolds, generally called mixed-dimensional partial differential equations. More recently he has successfully applied data-driven model reduction techniques to accelerate the numerical approximation of these models, making them available in real time, an enabling technology for the development of digital twins.  These models have been instrumental in studying the impact of treatments like radiotherapy, chemotherapy, and immunotherapy. He has co-authored more than 130 publications on mathematical modeling and computational methods applied various fields of engineering and life sciences.\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\nThu. October 24, 2024 at 16:00H (Berlin time)\nWHERE\nOn-site / Online\n[On-site]\nFriedrich-Alexander-Universität Erlangen-Nürnberg.\nRoom H2 (11202.00.305)\nH2 Egerlandstr.3 Anorganische Chemie\nEgerlandstraße 3, 91058 Erlangen\nGPS-Koord. Raum: 49.574538N, 11.028194E\n[Online]\nFAU Zoom link\nMeeting ID: 680 1463 6900 | PIN code: 222990\nThis event on LinkedIn\n \nYou might like:\n• FAU MoD Lectures\n• FAU MoD Lecture: Thoughts on Machine Learning by Prof. Dr. Rupert Klein\n• FAU MoD Lecture: Discovering and Communicating Excellence by Prof. Dr. Ute Klammer\n• FAU MoD Lecture: Using system knowledge for improved sample efficiency in data-driven modeling and control of complex technical systems by Prof. Dr. Sebastian Peitz\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 \n_\nDon’t miss out our last news and connect with us!\nwww.mod.fau.eu/events ( http://www.mod.fau.eu/events )\nLinkedIn | X (Twitter) | Instagram\n
URL:https://cmc.deusto.eus/events-calendar/fau-mod-lecture-new-avenues-for-the-interaction-of-computational-mechanics-and-machine-learning/
ORGANIZER;CN=FAU MoD:MAILTO:
CATEGORIES:FAU MoD Lecture,Seminar/Talk
LOCATION:Worldwide
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