Direttore Vicario: Prof. Gabriele Grillo
Responsabile Gestionale: Dr.ssa Franca Di Censo


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Prossimi Seminari

  • Optimal portfolio choice with delayed dynamics
    Cecilia Prosdocimi,  –
    martedì 28 novembre 2017 alle ore 14:00, Aula Seminari del Terzo Piano
  • Motori a reazione e razzi – La propulsione nell’atmosfera e fuori di essa
    Marco Beghi, Politecnico di Milano
    mercoledì 29 novembre 2017 alle ore 15:00, Sala Consiglio VII piano, Dip. di Matematica
  • Numerical simulations of non-ideal compressible-fluid flows
    Alberto Guardone, Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano
    giovedì 30 novembre 2017 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
  • A sharp Bernstein-type theorem for entire minimal graphs
    Alberto Farina, Université de Picardie
    martedì 5 dicembre 2017 alle ore 15:15, Sala Consiglio 7° piano
  • Testing for a significance in spatial regression with functional response
    Veronika Rímalová, Palacký University Olomouc, Czech Republic – Department of Mathematical Analysis and Applications
    martedì 5 dicembre 2017 alle ore 14:30, Aula Saleri VI Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
  • Five Decades of Time Parallel Time Integration: Best Current Methods for Parabolic and Hyperbolic Problems
    Martin Gander, Section de Mathématiques, Université de Geneve
    giovedì 14 dicembre 2017 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
  • Long-range phase transitions and minimal surfaces
    Serena Dipierro, Università degli Studi di Milano
    martedì 19 dicembre 2017 alle ore 15:15, Aula seminari 3° piano
  • Combining in vitro and in silico approaches towards patient-specific cardiovascular investigations
    Gabriele Dubini, Department of Chemistry, Materials and Chemical Engineering G. Natta, Politecnico di Milano
    giovedì 18 gennaio 2018 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
  • La matematica computazionale applicata alla medicina: risposte quantitative a diversi problemi clinici
    Christian Vergara, Politecnico di Milano
    mercoledì 31 gennaio 2018 alle ore 15:00, Sala Consiglio VII piano, Dip. di Matematica
  • Regularization Theory and Applications to Photoacoustic Imaging
    Otmar Scherzer, University of Vienna and Radon Institute of Computational and Applied Mathematics (Linz), Austria
    giovedì 8 febbraio 2018 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
  • Understanding Heart Tissue through Waves
    D. Nordsletten, Biomedical Engineering Department, King’s College, London
    giovedì 15 febbraio 2018 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
  • Models, Simulation, Uncertainty, and Medicine – Numerical Methods in Computational Biomechanics and Cardiology
    Rolf Krause, Center for Computational Medicine in Cardiology, Università della Svizzera italiana,
    giovedì 22 febbraio 2018 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO

Seminari Passati

  • Multi-scale and multi-physics modeling of complex flow and transport processes for energy storage in the subsurface
    Rainer Helmig, Department of Hydromechanics and Modelling of Hydrosystems, University of Stuttgart
    giovedì 23 novembre 2017 alle ore 14:00, Aula Consiglio VII Piano – Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
    The subsurface is being increasingly utilised both as a resource and as an energy and waste repository. Historically, there have been few issues of concern related to competition between resources, with groundwater contamination being a notable exception. However, with increasing exploitation, resource conflicts are becoming increasingly common and complex. Current issues in this regard include, for example, the long-range impact of mechanical, chemical and thermal energy storage on groundwater resources, and the complex effects surrounding hydraulic fracturing in both geothermal and shale gas production.
    To analyse and predict the mutual influence of subsurface projects and their impact on groundwater reservoirs, advanced numerical models are necessary. In general, these subsurface systems include processes of varying complexity occurring in different parts of the domain of interest. These processes mostly take place on different spatial and temporal scales. It is extremely challenging to model such systems in an adequate way, accounting for the spatially varying and scale-dependent character of these processes.
    In this seminar, we will give an overview of possible utilisation conflicts in subsurface systems and of how the groundwater is affected and review several model coupling concepts with a focus on the lecturer’s work in this field. The concepts are divided into temporal and spatial coupling concepts, where the latter are sub-divided into multi-process, multi-scale, multi-dimensional, and multi-compartment coupling strategies. We will present a large-scale simulation showing the general applicability of the modelling concepts of such complicated natural systems, especially the impact on the groundwater of simultaneously using geothermal energy and storing chemical and thermal energy. At the same time, we will show that such real large-scale systems provide a good environment for balancing the efficiency potential and possible weaknesses of the approaches discussed.


  • On segmentation with hidden, pairwise and triplet Markov models
    Juri Lember, University of Tartu, Estonia
    giovedì 23 novembre 2017 alle ore 10:00, Aula Seminari III piano
    The well-known hidden Markov model (HMM) is a two-dimensional stochastic process (X,Y), where Y is a Markov chain and conditionally on Y, the X-process consists of independent random variables, the distribution of the random variable X_t depending on Y_t, only. Over the last decades, HMM’s have become very popular stochastic models with applications to speech recognition, signal processing, linguistic, computational molecular biology and so on. Often the Y-process is unobserved (hidden) and the goal of the inference is to estimate its unobserved realization based on a realization of X-process. This task is called the segmentation problem and the standard ways to solve it is to use either maximum likelihood (so-called Viterbi) path or pointwise maximum likelihood (so-called PMAP) path.

    A trivial but important property of HMM is that the process Z=(X,Y) is itself a Markov process with a product state space. This observation allows naturally enlarge the class of HMM’s to the class of pairwise Markov models (PMM) as follows: Z=(X,Y) is a PMM if Z has Markov property. Now it is clear that PMM’s are a much larger class of models whose HMM’s is just a little subclass. We briefly discuss several PMM’s like Markov switching models and HMM’s with dependent noise. It is important to note that if (X,Y) is a Markov process, then neither X nor Y need to have Markov property, but conditionally on X, the Y-process is Markov and vice versa.
    It turns out that many good properties of HMM’s are mainly due to the Markov property of Z and hence these properties carry on to PMM’s as well. In particular the well-known Viterbi and forward-backward algorithms apply and so standard segmentation approaches can be applied in the case of PMM’s. Moreover, PMM-models provide a rather flexible and realistic model for the homology of random sequences. A triplet Markov model (TMM), introduced by W. Pieczynski, is a three-dimensional Markov process (X,Y,U), where, as previously, X stands for observations and Y is the hidden state sequence of interest. But in addition, there is another hidden component U. Since conditionally on U, the pair (X,Y) is an inhomogeneous PMM, the U-component models now the change of environment. It turns out that adding the U-component makes the model really flexible.

    We give a general approach to the risk-based segmentation problem that also applies for PMM’s and TMM’s, discuss the weaknesses standard approaches and introduce a way to overcome these problems. We also discuss the asymptotics of Viterbi segmentation for PMM’s.
  • A variational approach to the Mean Field Planning Problem
    Carlo Orrieri, Università di Roma La Sapienza
    martedì 21 novembre 2017 alle ore 15:15, Aula seminari 3° piano
    In the talk we deal with the so-called mean field planning problem: a coupled system of two PDEs, a forward continuity equation and a backward Hamilton-Jacobi equation. This problem has been introduced by P-L. Lions in a series of lectures held at Collège de France and can be viewed as a modification of the mean field games system as well as a generalization of the optimal transportation problem in its dynamic formulation à la Benamou-Brenier. We concentrate on the variational structure of the problem, from which a notion of “weak variational” solution can be given. In particular, we provide a well-posedness result for the system on the whole space in a $L^p$ framework under general assumptions on the coupling term.
    The talk is based on a joint work with G. Savaré and A. Porretta.
    Felix Otto, Max Plank Institute, Leipzig
    lunedì 20 novembre 2017 alle ore 16:30, Aula Chisini, via Saldini 50
  • A market consistent framework for the fair evaluation of insurance contracts under Solvency II
    Anna Maria Gambaro, Università del Piemonte Orientale
    lunedì 20 novembre 2017 alle ore 14:00, Aula Seminari del Terzo Piano
  • Unstructured meshing of geological domains – the RING perspective
    Guillaime Caumon, Université de Lorraine and member of the RING Team
    venerdì 17 novembre 2017 alle ore 10:00, Aula Consiglio VII piano, Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
    Numerical meshes are essential components for forecasting the physical behavior of subsurface domains. Structured grids are often used for this purpose, but they lack flexibility to accurately represent complex subsurface geometry and to provide local level of detail in heterogeneous media. Unstructured meshes can, in principle, address these two gaps. In spite of much progress, challenges still exist to easily create unstructured meshes whose features are compatible with geological heterogeneities, with the physics to be simulated and with the selected numerical method. In this talk, I will review some recent and ongoing work RING to address these problems and discuss some of the remaining challenges. I will also highlight some features of the RINGMesh library, which is as a platform to address mesh-related problems.

  • Un metodo Hybrid High-Order per problemi di piastre in flessione
    Francesco Bonaldi , MOX, Dipartimento di Matematica, Politecnico di Milano
    giovedì 16 novembre 2017 alle ore 10:00, Aula Saleri VI piano, Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
    In questo seminario verrà presentato un nuovo metodo di discretizzazione per problemi ellittici del quart’ordine tipici della meccanica delle piastre di Kirchhoff–Love, comprendenti l’equazione biarmonica come caso particolare. Il metodo proposto supporta ordini d’approssimazione arbitrari su griglie poligonali generali, e riproduce i principi chiave di equilibrio meccanico localmente, in ogni elemento della griglia. Se si utilizzano polinomi di grado $k \ge 1$ come incognite, il metodo converge in $h^{k+1}$ (con $h$, al solito, la spaziatura della griglia) in norma d’energia. Un ingrediente fondamentale nella dimostrazione della proprietà di convergenza è costituito da nuovi risultati di approssimazione per il proiettore biarmonico obliquo su spazi polinomiali locali. Inoltre, sotto ipotesi di regolarità biarmonica, si ottiene una stima in $h^{k+3}$ della norma $L^2$ dell’errore sulla deflessione. I risultati teorici sono supportati da prove numeri! che. La presentazione è basata su un lavoro in collaborazione con Giuseppe Geymonat (École Polytechnique), Daniele A. Di Pietro e Françoise Krasucki (Montpellier).

  • Inverse problems for PDE via infinite dimensional compressed sensing
    Matteo Santacesaria, Politecnico di Milano
    martedì 14 novembre 2017 alle ore 15:15, Aula seminari 3° piano
    Compressed sensing stands for a series of techniques whose aim is to recover a sparse signal from a small number of measurements. Since the 2006 seminal papers of Candes-Romberg-Tao and Donoho, which concerned the recovery of a sparse vector from few discrete Fourier coefficients, the subject has been extensively studied and generalized. In this talk we will present new results concerning generalization of compressed sensing in the framework of Hilbert spaces: in particular, the measurement operator does not need to be a orthonormal transformation and the unknown is assumed to be sparse in a frame. Applications to inverse problems for PDE, such as electrical impedance tomography, will be discussed as well. This is a joint work with Giovanni S. Alberti.