Upcoming events
  • jun 19 wed 2024

    jun 21 fri 2024

    WorkShop
    Kickoff workshop of the erc synergy grant ''nemesis: new generation methods for numerical simulations''
    06/19/2024 - 06/21/2024
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    • WORKSHOP
    • NEMESIS Kickoff Workshop
    • organizers
      Paola F. Antonietti (Politecnico di Milano), Lourenco Beirao da Veiga (Università degli Studi di Milano-Bicocca), Daniele A. Di Pietro (Université de Montpellier), Jerome Droniou (CNRS)
    • The ERC NEMESIS project has been funded in the 2023 Synergy call for a duration of six years. Its goal is to lay the groundwork for a novel generation of numerical simulators by tackling key difficulties of PDE problems of the 21st century: -Incomplete differential operators in Hilbert complexes; -The efficient solution of the discrete problems relating to the latter; -The presence of nonlinear and hybrid-dimensional multi-physics, encountered in applications such as geological flows or magneto-hydrodynamics. The NEMESIS project aims at overcoming the above difficulties, therefore boosting the prediction capabilities of numerical simulators in engineering and applied sciences. A key point will be the use of polytopal meshes and the higher-level point of view provided by polytopal constructions. This kick-off workshop will gather a community of mathematicians and engineers working in the broad field of the project, to foster exchanges and promote long-term collaborations.
    • Wednesday, 19 June 2024 - Friday, 21 June 2024
      Montpellier (FR)
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • jul 02 tue 2024

    MOX Seminar
    Patrick Vega, An adaptive superconvergent mixed finite element method based on local residual minimization,  07-02-2024, 14:00
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    MOX
    MOX Numeth

    • MOX Seminar
    • Patrick Vega
    • Universidad de Santiago de Chile
    • An adaptive superconvergent mixed finite element method based on local residual minimization
    • Tuesday, 2 July 2024 at 14:00
    • Aula Saleri
    • Abstract
      We introduce an adaptive superconvergent finite element method for a class of mixed formulations to solve partial differential equations involving a diffusion term. It combines a superconvergent postprocessing technique for the primal variable with an adaptive finite element method via residual minimization. Such a residual minimization procedure is performed on a local postprocessing scheme, commonly used in the context of mixed finite element methods. Given the local nature of that approach, the underlying saddle point problems associated with residual minimizations can be solved with minimal computational effort. We propose and study a posteriori error estimators, including the built-in residual representative associated with residual minimization schemes; and an improved estimator that adds, on the one hand, a residual term quantifying the mismatch between discrete fluxes and, on the other hand, the interelement jumps of the postprocessed solution. We present numerical experiments in two dimensions using Brezzi-Douglas-Marini elements as input for our methodology. The experiments perfectly fit our key theoretical findings and suggest that our estimates are sharp.

      Contatto:
      michele.botti@polimi.it
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • jul 04 thu 2024

    jul 05 fri 2024

    WorkShop
    Hpcsim - frontiers of high-performance computing in modeling and simulation
    07/04/2024 - 07/05/2024
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    • WORKSHOP
    • HPCSIM2024
    • organizers
      Luca Formaggia, Paolo Cremonesi, Carlo de Falco, Ivan Fumagalli, Ilario Mazzieri, Nicola Parolini (Politecnico di Milano), Carlo Janna, Andrea Franceschini (Università di Padova), Nicolò Spiezia (M3E)
    • HPCSIM aims to explore recent methodologies to accelerate simulation software on massively parallel platforms and provide researchers and practitioners with a survey on the potential of HPC in real-world applications. Registration at https://www.mate.polimi.it/events/HPCSIM24/"
    • Thursday, 4 July 2024 - Friday, 5 July 2024
      Politecnico di Milano, Leonardo Campus - Aula Rogers
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • jul 12 fri 2024

    jul 15 mon 2024

    WorkShop
    Gdfgdfg
    07/12/2024 - 07/15/2024
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    • WORKSHOP
    • organizers
      sdfsf
    • dgdfgdfg
    • Friday, 12 July 2024 - Monday, 15 July 2024
      sdfsdf
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • aug 10 sat 2024

    aug 13 tue 2024

    WorkShop
    Gdfgd
    08/10/2024 - 08/13/2024
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    • WORKSHOP
    • organizers
      dfgdg
    • dfgdg
    • Saturday, 10 August 2024 - Tuesday, 13 August 2024
      dgdg
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • aug 15 thu 2024

    aug 18 sun 2024

    WorkShop
    Titolo
    08/15/2024 - 08/18/2024
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    • WORKSHOP
    • organizers
      Organizzatori
    • Descrizione
    • Thursday, 15 August 2024 - Sunday, 18 August 2024
      Luogo
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • sep 09 mon 2024

    sep 11 wed 2024

    WorkShop
    13th symposium on conformal and probabilistic prediction with applications
    09/09/2024 - 09/11/2024
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    • WORKSHOP
    • COPA 2024
    • organizers
      Simone Vantini (General Chair); Matteo Fontana (Programme Chair); Alfredo Gimenez Zapiola, Teresa Bortolotti, Khuong An Nguyen (Organizing Chairs); Francesca Ieva (Stakeholder Relation Chair)
    • Conformal prediction (CP) is a modern machine and statistical learning method that allows to develop valid predictions under weak probabilistic assumptions. CP can be used to form set predictions, using any underlying point predictor, and for very general target variables, allowing the error levels to be controlled by the user. Therefore, CP has been widely used to develop robust forms of probabilistic prediction methodologies, and applied to many practical real life challenges. The aim of this symposium is to serve as a forum for the presentation of new and ongoing work and the exchange of ideas between researchers on any aspect of conformal and probabilistic prediction, including their application to interesting problems in any field.
    • Monday, 9 September 2024 - Wednesday, 11 September 2024
      Politecnico di Milano
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • sep 19 thu 2024

    MOX Colloquia
    Jay Gopalakrishnan, From scalar to tensor finite elements,  09-19-2024, 14:00
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    MOX

    • MOX Colloquia
    • Jay Gopalakrishnan
    • Portland State University
    • From scalar to tensor finite elements
    • Thursday, 19 September 2024 at 14:00
    • Aula Consiglio VII piano - Dipartimento di Matematica
    • Abstract
      In the history of finite elements, the earliest Lagrange finite elements, consisted of scalar-valued functions. To approximate fluxes, vector-valued finite elements with continuous normal (n) components across element interfaces, or n-continuous elements, were developed later. The finite element toolkit was then supplemented by t-continuous vector-valued Nedelec elements with continuous tangential (t) components, now routinely used for Maxwell equations. Although these elements were developed separately, today we understand them together as fitting into a cochain subcomplex of a de Rham complex of Sobolev spaces.
      Other tensor-valued finite elements are now being viewed with increasing interest and they form the main subject of this talk. The earliest of these consists of matrix-valued functions whose normal-normal (nn) component varies continuously across element interfaces: these are the nn-continuous matrix fields of the Hellan-Herrmann-Johnson element. More recently, nt-continuous matrix-valued finite elements were developed to approximate viscous stress in incompressible flows: they have continuous shear, or normal-tangential (nt) components. To add to this picture, matrix-valued elements with continuous tangential-tangential (tt) components, called Regge elements, are finding increasing utility: they are key to approximating the metric tensor of Riemannian manifolds. This talk delves into the details of these developments.
      How does one connect these disparate developments with nn-, nt-, and tt-continuous matrix finite elements? This does not appear to be as easy as the previous synthesis of vector-valued elements by the de Rham complex. The spaces in de Rham complexes are connected by fundamental first-order differential operators (grad, curl, and div in three dimensions), all derived from a single definition of the exterior derivative. In contrast, what is natural for the above-mentioned tensor finite elements are other second-order differential operators. We conclude grazing the frontiers of our understanding on potentially unifying connections.

      This initiative is part of the “Ph.D. Lectures” activity of the project "Departments of Excellence 2023-2027" of the Department of Mathematics of Politecnico di Milano. This activity consists of seminars open to Ph.D. students, followed by meetings with the speaker to discuss and go into detail on the topics presented at the talk.

      Contatti:
      paola.antonietti@polimi.it
      gabriele.ciaramella@polimi.it
      ilario.mazzieri@polimi.it
    • Jay Gopalakrishnan

      Jay Gopalakrishnan

      Jay Gopalakrishnan is a computational mathematician whose research centers around improving accuracy and efficiency of finite element methods for partial differential equations. He co-invented two classes of numerical methods, now known as the discontinuous Petrov Galerkin (DPG) methods, and the hybridizable discontinuous Galerkin (HDG) methods. He has co-authored over ninety publications, has served in the editorial boards of seven journals, including service as one of the managing editors. He earned his PhD in 1999 under the supervision of James Bramble and Joseph Pasciak He then worked at Bell Labs, Medtronic Inc, University of Minnesota, and was a mathematics professor at University of Florida for over a decade. He currently holds an endowed chair at Portland State University in Oregon, where he is engaged in a variety of regional activities to bolster scientific computation.
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • oct 11 fri 2024

    oct 16 wed 2024

    WorkShop
    Titolo
    10/11/2024 - 10/16/2024
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    • WORKSHOP
    • organizers
      Organizzatori
    • Descrizione
    • Friday, 11 October 2024 - Wednesday, 16 October 2024
      Luogo
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • oct 12 sat 2024

    oct 15 tue 2024

    WorkShop
    Dgdg
    10/12/2024 - 10/15/2024
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    • WORKSHOP
    • organizers
      dgdg
    • fdgdfg
    • Saturday, 12 October 2024 - Tuesday, 15 October 2024
      dfgdg
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • oct 14 mon 2024

    oct 17 thu 2024

    WorkShop
    Gsdgsg
    10/14/2024 - 10/17/2024
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    • WORKSHOP
    • organizers
      sgsgs
    • sgsg
    • Monday, 14 October 2024 - Thursday, 17 October 2024
      sdgsdg
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • oct 14 mon 2024

    oct 21 mon 2024

    WorkShop
    Fsfs
    10/14/2024 - 10/21/2024
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    • WORKSHOP
    • organizers
      sdfsf
    • sdfsdf
    • Monday, 14 October 2024 - Monday, 21 October 2024
      sdfsdf
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • oct 17 thu 2024

    MOX Colloquia
    Marc G. Genton, Exascale Geostatistics for Environmental Data Science,  10-17-2024, 14:00
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    MOX

    • MOX Colloquia
    • Marc G. Genton
    • King Abdullah University of Science and Technology (KAUST), Saudi Arabia
    • Exascale Geostatistics for Environmental Data Science
    • Thursday, 17 October 2024 at 14:00
    • Aula Consiglio VII piano - Dipartimento di Matematica
    • Abstract
      Environmental data science relies on some fundamental problems such as: 1) Spatial Gaussian likelihood inference; 2) Spatial kriging; 3) Gaussian random field simulations; 4) Multivariate Gaussian probabilities; and 5) Robust inference for spatial data. These problems develop into very challenging tasks when the number of spatial locations grows large. Moreover, they are the cornerstone of more sophisticated procedures involving non-Gaussian distributions, multivariate random fields, or space-time processes. Parallel computing becomes necessary for avoiding computational and memory restrictions associated with large-scale environmental data science applications. In this talk, I will explain how high-performance computing can provide solutions to the aforementioned problems using tile-based linear algebra, tile low-rank approximations, as well as multi- and mixed-precision computational statistics. I will introduce ExaGeoStat, and its R version ExaGeoStatR, a powerful software that can perform exascale (10^18 flops/s) geostatistics by exploiting the power of existing parallel computing hardware systems, such as shared-memory, possibly equipped with GPUs, and distributed-memory systems, i.e., supercomputers. I will then describe how ExaGeoStat can be used to design competitions on spatial statistics for large datasets and to benchmark new methods developed by statisticians and data scientists for large-scale environmental data science.

      Contatti: laura.sangalli@polimi.it
    • Marc G. Genton

      Marc G. Genton

      Marc G. Genton is Al-Khawarizmi Distinguished Professor of Statistics at the King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. He received the Ph.D. degree in Statistics (1996) from the Swiss Federal Institute of Technology (EPFL), Lausanne. He is a fellow of the American Statistical Association (ASA), of the Institute of Mathematical Statistics (IMS), and the American Association for the Advancement of Science (AAAS), and is an elected member of the International Statistical Institute (ISI). In 2010, he received the El-Shaarawi award for excellence from the International Environmetrics Society (TIES) and the Distinguished Achievement award from the Section on Statistics and the Environment (ENVR) of the American Statistical Association (ASA). He received an ISI Service award in 2019 and the Georges Matheron Lectureship award in 2020 from the International Association for Mathematical Geosciences (IAMG). He led a Gordon Bell Prize finalist team with the ExaGeoStat software for Super Computing 2022. He received the Royal Statistical Society (RSS) 2023 Barnett Award for his outstanding research in environmental statistics. His research interests include statistical analysis, flexible modeling, prediction, and uncertainty quantification of spatio-temporal data, with applications in environmental and climate science, as well as renewable energies.
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • nov 21 thu 2024

    MOX Colloquia
    Klaus-Robert Müller, Machine Learning and AI for the Sciences: toward understanding,  11-21-2024, 14:00
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    MOX

    • MOX Colloquia
    • Klaus-Robert Müller
    • Technische Universität Berlin
    • Machine Learning and AI for the Sciences: toward understanding
    • Thursday, 21 November 2024 at 14:00
    • Aula Consiglio VII piano
    • Abstract
      In recent years, machine learning (ML) and artificial intelligence (AI) methods have begun to play a more and more enabling role in the sciences and in industry. In particular, the advent of large and/or complex data corpora has given rise to new technological challenges and possibilities. In his talk, Müller will touch upon the topic of ML applications in the sciences, in particular in chemistry and physics. He will also discuss possibilities for extracting information from machine learning models to further our understanding by explaining nonlinear ML models. Finally, Müller will briefly discuss perspectives and limitations.
    • Klaus-Robert Müller

      Klaus-Robert Müller

      Klaus-Robert Müller has been a professor of computer science at Technische Universität Berlin since 2006; at the same time he is directing rsp. co-directing the Berlin Machine Learning Center and the Berlin Big Data Center and most recently BIFOLD . He studied physics in Karlsruhe from 1984 to 1989 and obtained his Ph.D. degree in computer science at Technische Universität Karlsruhe in 1992. After completing a postdoctoral position at GMD FIRST in Berlin, he was a research fellow at the University of Tokyo from 1994 to 1995. In 1995, he founded the Intelligent Data Analysis group at GMD-FIRST (later Fraunhofer FIRST) and directed it until 2008. From 1999 to 2006, he was a professor at the University of Potsdam. From 2012 he has been Distinguished Professor at Korea University in Seoul. In 2020/2021 he spent his sabbatical at Google Brain as a Principal Scientist. Among others, he was awarded the Olympus Prize for Pattern Recognition (1999), the SEL Alcatel Communication Award (2006), the Science Prize of Berlin by the Governing Mayor of Berlin (2014), the Vodafone Innovations Award (2017), Hector Science Award (2024), Pattern Recognition Best Paper award (2020), Digital Signal Processing Best Paper award (2022). In 2012, he was elected member of the German National Academy of Sciences-Leopoldina, in 2017 of the Berlin Brandenburg Academy of Sciences, in 2021 of the German National Academy of Science and Engineering and also in 2017 external scientific member of the Max Planck Society. From 2019 on he became an ISI Highly Cited researcher in the cross-disciplinary area. His research interests are intelligent data analysis and Machine Learning in the sciences (Neuroscience (specifically Brain-Computer Interfaces, Physics, Chemistry) and in industry.
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • nov 22 fri 2024

    nov 27 wed 2024

    WorkShop
    Fsdf
    11/22/2024 - 11/27/2024
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    • WORKSHOP
    • organizers
      sfsf
    • sdfdsf
    • Friday, 22 November 2024 - Wednesday, 27 November 2024
      sfsf
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568