PhD Courses

Courses 2023-24
SSD Name of the course Professor Semester Language Credits
MAT/05
(BA)
Stability and instability in dynamical systems Giuliani Fall English 5
SECS-S/01
(BA)
Advanced statistical learning for complex data Ieva Fall English 5
MAT/08
(BA)
Mathematical and numerical foundations of scientific machine learning Pagani, Miglio Fall English 5
MAT/05, MAT/07
(SC)
Spectral and scattering theory in quantum mechanics Borrelli, Fermi Spring English 5
MAT/08
(SC)
Advanced numerical methods for predictive digital twins Fresca, Zunino Spring English 5
MAT/05
(SC)
Mathematical Aspects of Fluid Mechanics Giorgini Fall English 5
MAT/06
(SC)
An introduction to the Malliavin calculus Zanella Fall English/Italiano 5
  Advanced mathematical methods in engineering I Correggi Spring/Fall   5
  Advanced mathematical methods in engineering II Correggi Spring/Fall   5
Upcoming events
  • apr 04 thu 2024

    Seminar
    Eliseo Luongo, Global Well-Posedness and Interior Regularity of 2D Navier-Stokes Equations with Stochastic Wind Driven Boundary Conditions,  04-04-2024, 11:30
    logo matematica
    • Seminar
    • Eliseo Luongo
    • Scuola Normale Superiore, Pisa
    • Global Well-Posedness and Interior Regularity of 2D Navier-Stokes Equations with Stochastic Wind Driven Boundary Conditions
    • Thursday, 4 April 2024 at 11:30
    • Aula Seminari MOX - VI piano
    • Abstract
      Partial differential equations with boundary noise have been introduced by Da Prato and Zabczyck. They showed that, also in the one dimensional case, the solutions of the heat equation with white noise Dirichlet or Neumann Boundary conditions have low regularity compared to the case of noise diffused inside the domain. In particular, in the case of Dirichlet boundary conditions the solution is only a distribution. Some improvements in the analysis of the interior regularity of the solutions of these problems and some nonlinear variants have been obtained exploiting specific properties of the heat kernel and of suitable nonlinearities. All these issues make the problem of treating non-linear partial differential equations with boundary noise coming from fluid dynamical models an, almost untouched, field of open problems. In this talk we discuss the global well-posedness and the interior regularity of a system of 2D Navier-Stokes equations with inhomogeneous stochastic boundary conditions. The noise, white in time and coloured in space, can be interpreted as the physical law describing the driving mechanism on the atmosphere-ocean interface, i.e. as a balance of the shear stress of the ocean and the horizontal wind force. The talk is based on a joint work with A. Agresti.
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • apr 04 thu 2024

    MOX Seminar
    Lorenzo Tamellini, Combining noisy well data and expert knowledge in a Bayesian calibration of a flow model under uncertainties: an application to solute transport in the Ticino basin,  04-04-2024, 15:30
    logo matematica
    MOX
    MOX Numeth

    • MOX Seminar
    • Lorenzo Tamellini
    • CNR-IMATI Pavia
    • Combining noisy well data and expert knowledge in a Bayesian calibration of a flow model under uncertainties: an application to solute transport in the Ticino basin
    • Thursday, 4 April 2024 at 15:30
    • Aula Saleri
    • Abstract
      In this talk we present the results of a case-study aimed at providing a UQ analysis of solute travel times in groundwater in the basin of the Ticino River (northern Italy), starting from well data collected over a month in summer 2014. We consider a steady-state groundwater flow model (developed in MODFLOW) and perform a sensitivity analysis using the Morris method to discard uninfluential parameters. We then employ Bayesian inversion (with Gaussian approximation) to obtain a data-informed posterior pdf for the remaining parameters, and propagate these pdfs to travel times computed by particle tracking (MODPATH). The likelihood function employed in the Bayesian inversion takes into account both well measurements and expert knowledge about the extent of the springs in the domain under study.

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

  • apr 11 thu 2024

    MOX Seminar
    Michele Benzi, Revisiting the Augmented Lagrangian Approach to Saddle-Point Problems,  04-11-2024, 14:00
    logo matematica
    MOX
    MOX Numeth

    • MOX Seminar
    • Michele Benzi
    • Scuola Normale Superiore, Pisa
    • Revisiting the Augmented Lagrangian Approach to Saddle-Point Problems
    • Thursday, 11 April 2024 at 14:00
    • Online (trasmesso anche in aula Saleri)
    • Abstract
      Augmented Lagrangian (AL) methods have a long history in both optimization and numerical PDEs, going back to the work of Powell and Hestenes in the late 1960s and to the work of Glowinski and collaborators starting in the mid-1970s, respectively. Whereas AL-type methods have been long very popular in the field of constrained optimization, where are among the most widely used techniques available (as witnessed, for instance, by the great success enjoyed by methods like ADMM), the track record of these methods in solving PDE-related problems has been until recently somewhat less impressive, due in part to ill-conditioning and implementation difficulties.
      In this talk I will describe advances in developing robust and scalable solvers for PDE-related saddle point problems by means of iterative methods and block preconditioners tailored to the AL formulation. The effectiveness of these solvers will be demonstrated on problems from incompressible flow (Oseen problem, coupled Stokes-Darcy problem), liquid crystal directors modeling, and optimal control with PDE constraints. Collaborators over the years include Fatemeh Beik, Chiara Faccio, Patrick Farrell, Santolo Leveque, Maxim Olshanskii and Zhen Wang.

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

  • apr 11 thu 2024

    Seminar
    Giovanni Cupini, The Leray-Lions existence theorem under (p,q)-growth conditions,  04-11-2024, 15:00
    logo matematica
    • Seminar
    • Giovanni Cupini
    • Università di Bologna
    • The Leray-Lions existence theorem under (p,q)-growth conditions
    • Thursday, 11 April 2024 at 15:00
    • Aula Seminari - III Piano
    • Abstract
      In this talk I will describe recent results obtained in collaboration with P. Marcellini and E. Mascolo. In particular, we proved an existence result of weak solutions to a Dirichlet problem associated to second order elliptic equations in divergence form satisfying (p,q)-growth conditions. This is a first attempt to extend to (p,q)-growth the well known Leray-Lions existence theorem, which holds under the so-called natural growth conditions.
      Our existence result is obtained "via regularity", i.e., by using new local regularity results (boundedness, Lipschitz continuity and higher differentiability) for the weak solutions of the associated equation.
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • apr 16 tue 2024

    Seminar
    Barbara Guardabascio, Climate and environmental attention: a news-based composite indicator,  04-16-2024, 16:30 precise
    logo matematica
    • Seminar
    • Barbara Guardabascio
    • Università Perugia
    • Climate and environmental attention: a news-based composite indicator
    • Tuesday, 16 April 2024 at 16:30 right
    • Politecnico di Milano Aula IV (accanto aula Rogers)
    • Abstract
      The way people perceive the risks associated with climate change is influenced by scientific research, social awareness, and by media representation Boykoff [2011]. The effects of perception of climate risk extend beyond Environmental concerns and permeate decision-making processes in both economic and social policy.
      We believe that a composite index to measure climate attention, if well-constructed and robust, can provide valuable insights for policymakers and serve as a leading indicator in macroeconomic and financial analysis [Luxon, 2019]. The composite indicator proposed in this article is based on a novel methodology that evaluates the semantic relevance, and not the favorability, of selected keywords, each of them provided with a semantic score, based both on the number of appearances and on the interconnectedness with other words in the text corpus.
      Finally, the Benefit of the Doubt (BoD) aggregation strategy is adopted that takes advantage of a time-varying optimal weighting scheme. The index is compared to alternative approaches.
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • apr 16 tue 2024

    Seminar
    Viola Schiaffonati, L'etica dell'intelligenza artificiale fra vecchi problemi e nuove sfide,  04-16-2024, 17:30
    logo matematica
    • Seminar
    • Viola Schiaffonati
    • Politecnico di Milano
    • L'etica dell'intelligenza artificiale fra vecchi problemi e nuove sfide
    • Tuesday, 16 April 2024 at 17:30
    • Aula Rogers e in collegamento webex su tiny.cc/mathseminars
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • apr 18 thu 2024

    Seminar
    Elena Danesi, Strichartz estimates for the Dirac equation on compact manifolds without boundary,  04-18-2024, 15:00
    logo matematica
    • Seminar
    • Elena Danesi
    • Università di Padova
    • Strichartz estimates for the Dirac equation on compact manifolds without boundary
    • Thursday, 18 April 2024 at 15:00
    • Aula seminari - III piano
    • Abstract
      The Dirac equation on Rn can be listed within the class of dispersive equations, together with, e.g., the wave and Klein-Gordon equations. In the years a lot of tools have been developed in order to quantify the dispersion of a system. Among these one finds the Strichartz estimates, that are a priori estimates of the solutions in mixed Lebesgue spaces. For the flat case Rn they are known, as they are derived from the ones that hold for the wave and Klein-Gordon equations. However, when passing to a curved spacetime domain, very few results are present in the literature. In this talk I will firstly introduce the Dirac equation on curved domains. Then, I will discuss the validity of this kind of estimates in the case of Dirac equations on compact Riemannian manifolds without boundary. This is based on a joint work with Federico Cacciafesta (Università di Padova) and Long Meng (CERMICS-École des ponts ParisTech).
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • may 06 mon 2024

    may 08 wed 2024

    WorkShop
    Meeting on tomography and applications discrete tomography, neuroscience and image reconstruction 18th edition
    05/06/2024 - 05/08/2024
    logo matematica
    • WORKSHOP
    • TAIR
    • organizers
      Paolo Dulio - Politecnico Milano, Paolo Finotelli – Université de Caen Normandie, Andrea Frosini - Universita' Firenze, Silvia Pagani - Universita' Cattolica,
    • The aim of the Meeting is to share interdisciplinary aspects between the experimental and the mathematical research concerning image reconstruction, with a special focus on tomography and neuroscience
    • Monday, 6 May 2024 - Wednesday, 8 May 2024
      Mathematics Department - 7th floor
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • may 06 mon 2024

    may 10 fri 2024

    WorkShop
    The geometry of hilbert schemes of points
    05/06/2024 - 05/10/2024
    logo matematica
    • WORKSHOP
    • GHiSP
    • organizers
      Michele Graffeo (SISSA), Paolo Lella (Polimi), Sergej Monavari (EPFL), Andrea T. Ricolfi (SISSA), Alessio Sammartano (Polimi)
    • The Hilbert scheme is a classically studied moduli space, which parametrises closed subschemes with prescribed Hilbert polynomial in an ambient projective scheme. These moduli spaces where initially introduced by Grothendieck, but turned out to have a prominent rôle in many modern areas outside the realm of Algebraic Geometry: Mathematical Physics, Combinatorics, Theoretical Physics (just to mention some recent examples). Generalisations of the Hilbert scheme have a wide range of applications as well, such as nested Hilbert schemes (parametrising flags of closed subschemes), moduli spaces of framed sheaves and Quot schemes (parametrising quotient sheaves). The easiest example one can consider is the Hilbert scheme of points, which parametrises closed zero-dimensional subschemes of fixed length. Already in this case, the geometry of the moduli space is rich and intriguing, as it is in general considerably pathological. For instance, if the dimension of the ambient variety is 3, the Hilbert scheme of points is in general reducible, and for dimension larger than 4 its singularities can be as bad as possible. Hilbert schemes (and their generalisation) played an important role in the development of modern Enumerative Geometry. In fact, for a large and interesting class of cases, the Hilbert scheme of points is not smooth but carries a virtual fundamental class. Donaldson-Thomas theory deals precisely with the (virtual) invariants one can compute on the Hilbert schemes with respect to its virtual structure. Donaldson-Thomas theory is very rich and admits several layers of refinements, for example: cohomological, K-theoretical, elliptic, categorical, motivic and is predicted to match Gromov-Witten invariants. SPEAKERS Alessandra Bernardi, Gergely Bérczi, Nadir Fasola, Anthony Iarrobino, Joachim Jelisiejew, Tomasz Mandziuk, Cristina Manolache, Alina Marian, Rosa Maria Miro-Roig, Andrei Negut, Ritvik Ramkumar, Ilaria Rossinelli, Reinier F. Schmiermann, Roy Skjelnes
    • Monday, 6 May 2024 - Friday, 10 May 2024
      BellaVista Relax Hotel, Levico Terme (TN), Italy
    Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568
  • may 07 tue 2024

    Seminar
    Annalisa Panati, Fisica a teatro: lo strano caso di Wolfgang Pauli,  05-07-2024, 17:30
    logo matematica
    • Seminar
    • Annalisa Panati
    • Università di Tolone
    • Fisica a teatro: lo strano caso di Wolfgang Pauli
    • Tuesday, 7 May 2024 at 17:30
    • Aula Rogers e in collegamento webex su tiny.cc/mathseminars
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • may 29 wed 2024

    Seminar
    Paolo Cremonesi, La magia dei Computer Quantistici,  05-29-2024, 17:30
    logo matematica
    • Seminar
    • Paolo Cremonesi
    • Politecnico di Milano
    • La magia dei Computer Quantistici
    • Wednesday, 29 May 2024 at 17:30
    • Aula T12 e in collegamento webex su tiny.cc/mathseminars
    • Politecnico di Milano, Dipartimento di Matematica ed. 14 "Nave", Piazza Leonardo da Vinci, 32, 20133 Milano, Telefono: +39 0223994505 - Fax: +39 0223994568

  • jun 05 wed 2024

    jun 07 fri 2024

    WorkShop
    Perspectives in pdes, global and functional analysis
    06/05/2024 - 06/07/2024
    logo matematica
    • WORKSHOP
    • organizers
      Matteo Bonforte (Universidad Autónoma de Madrid, Spain) Matteo Muratori (Politecnico di Milano, Italy) Fabio Punzo (Politecnico di Milano, Italy) Alberto Setti (Università degli Studi dell'Insubria, Italy)
    • This workshop aims at bringing together world experts from Analysis and Geometry, with a particular accent on the broad field of Partial Differential Equations and their applications. In particular, the main topics addressed lie at the interface between Global Analysis, Functional Analysis, Geometric Analysis and Differential Geometry. The meeting is held on the special occasion given by the 60th birthday of Gabriele Grillo, Professor of Mathematical Analysis at Politecnico di Milano since 2009.
    • Wednesday, 5 June 2024 - Friday, 7 June 2024
      Università degli Studi dell'Insubria - Sede di Sant'Abbondio a Como
    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
    logo matematica
    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

  • sep 19 thu 2024

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

      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 17 thu 2024

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