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One year post-doc position in Padova opening soon
by Giorgia Callegaro 01 Jul '26

01 Jul '26

Dear all, We are pleased to announce that a post-doctoral position will open after the summer break at the Department of Mathematics in Padova. The research topic focuses on *cyber security risk mitigation*, and the successful candidate will join the working team of Profs. Callegaro, D'Auria, and Fontana. All relevant (and available!) details can be found in the attached PDF. Please feel free to reach out if you have any questions. We look forward to receiving your applications! Best regards, Giorgia, Bernardo and Claudio Giorgia Callegaro Associate Professor Department of Mathematics - University of Padova Via Trieste 63 , I-35121 Padova - ITALY Tel: +39-0498271481 Fax: +39-0498271499 E-Mail: gcallega(a)math.unipd.it <https://webmail.math.unipd.it/horde3/imp/message.php?mailbox=Sent&index=598#> Personal web-page: https://sites.google.com/site/giogiocallegaro/Home

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Fwd: Assistant Professors in Mission-Driven Research on Future-Proof Networks at Eindhoven University of Technology
by Cristian GIARDINA' 30 Jun '26

30 Jun '26

Ricevo e volentieri inoltro. Cristian Giardina' ------------------ The Eindhoven University of Technology (TU/e), *Department of Mathematics & Computer Science* <https://www.youtube.com/watch?v=JQRS85BMQUY>(M&CS), invites applications for *three Assistant Professor (UD) positions*. Although this is a broadly advertised call, we are particularly interested in candidates with an MSc or PhD in Mathematics or Statistics who are strongly motivated to engage in mission‑driven research on Future‑Proof Networks. We are looking for researchers who are committed to delivering concrete results, developing proof‑of‑concepts, and demonstrating the impact of their work. Expertise in mathematical networks is considered a plus, and preference will be given to candidates whose research interests align with the mathematical foundations of networks. The application period runs until August 15. For more information and the application form, please see the *vacancy page* <https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact…>. We look forward to receiving your application.

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Frontiers in Risk and Investment Theory (FRIT 2026)
by Marco Maggis 30 Jun '26

30 Jun '26

Dear colleagues, this is the second announcement for the workshop *Frontiers in Risk and Investment Theory (FRIT 2026)*, which will take place at *Hotel La Palma*, Stresa (Lake Maggiore, Italy), on *September 20–22, 2026*. Confirmed speakers Beatrice Acciaio Francesca Biagini Bruno Dupire Hans Foellmer Jean-Pierre Fouque Fausto Gozzi Felix Liebrich Massimo Marinacci Thilo Meyer-Brandis Max Nendel Jan Obłój Frank Riedel Wolfgang Runggaldier Walter Schachermayer Martin Schweizer Nizar Touzi The conference will also be a special occasion to celebrate the 65th birthday of Marco Frittelli. Participation is free of charge, but registration is mandatory. The deadline for registration is *July 15, 2026*. Please note that the number of participants is limited. Further information is available at: https://sites.google.com/view/ <https://sites.google.com/view/frit2026> <https://sites.google.com/view/frit2026>frit2026 <https://sites.google.com/view/frit2026> We would be grateful if you could circulate this announcement among colleagues who may be interested. We look forward to welcoming you to Stresa. Best regards, The Organizing Committee

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SEMINARIO presso Politecnico di Milano - 13.07.26 ore 11:30 - Soumick Chatterjee
by Laura Maria Sangalli 29 Jun '26

29 Jun '26

Cari Colleghi, A seguire annuncio di un seminario organizzato presso il Laboratorio MOX - Politecnico di Milano: Soumick Chatterjee, Human Technopole 13.07.26 ore 11:30 – Aula Saleri Link: https://mox.polimi.it/mox-colloquia-seminars-list/mox-seminars/?id_evento=2… Titolo: A Chain of Estimation Problems in Medical Imaging: Probabilistic Modelling from Reconstruction to Genetics Abstract: A medical image is never observed directly. It is inferred from incomplete measurements, interpreted under genuine ambiguity, compressed into a usable description, and finally explained in terms of underlying biology. This talk uses that chain as its backdrop and takes up three distinct estimation problems situated at different points along it, each filling a different gap that the others leave open. The common stance is that each problem is best posed in terms of a distribution or an estimator rather than a single picture. The first problem is reconstruction, an ill-posed inverse problem: the image has to be recovered from far fewer measurements than there are unknowns, so the solution is not unique. Estimators that learn the prior structure of plausible images from data, while staying consistent with the measurements actually acquired, then single out a high-quality reconstruction. The second is interpretation under expert disagreement, where a single segmentation is untenable and the natural target becomes a predictive distribution, learned by matching expert variability through statistical divergences and assessed through calibration. The third is the move from image to biology: unsupervised generative models place whole-organ images on a low-dimensional manifold, yielding compact and reproducible descriptors of anatomy and function. Treated as quantitative phenotypes, these descriptors are then linked to the genome through heritability estimation and genome-wide association in tens of thousands of individuals, recovering and extending known genetic architecture. The thread throughout is that careful probabilistic and mathematical modelling, rather than any single method, is what turns images into biological insight. Un caro saluto a tutti, Laura Sangalli —— Laura Maria Sangalli MOX - Dipartimento di Matematica Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano - Italy (+39) 02 2399 4554 laura.sangalli(a)polimi.it https://sangalli.faculty.polimi.it

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Secondo ciclo di seminari online sulle applicazioni della probabilità in economia
by Enrico Scalas 29 Jun '26

29 Jun '26

Buongiorno, vi segnaliamo le date e i contenuti del secondo ciclo di seminari estivi online sulle applicazioni della probabilità in economia organizzate dal gruppo UMI PRISMA. 16 luglio 2026, ore 14 Daria Ghilli, Department of Economics and Management, University of Pavia Title: Mean Field Games in infinite dimensional spaces and applications to economics Abstract: We present an overview of mean field game models for large populations of forward-looking agents whose individual state is naturally infinite-dimensional. This situation arises when agents’ dynamics involve variables such as age, spatial position, memory or path-dependent effects, or delay. These features are common in economic applications, including vintage capital models, production planning problems, and systemic risk. We explain how infinite-dimensional techniques make it possible to reformulate such dynamics as abstract evolution equations in Hilbert spaces, often eliminating the explicit delay by enlarging the state variable. We then present some recent results and discuss applications to vintage capital models and systemic risk. 23 luglio 2026, ore 14 Miguel Angel Sordo Diaz, Departamento de Estadística e Investigación Operativa, Universidad de Cádiz Title: A Spearman-like coefficient for upper-tail association analysis Abstract: Quantifying association during extreme events is of paramount importance in fields such as finance, insurance, and environmental sciences. Classical correlation measures often fail to capture co-movements in the tails of distributions, while traditional boundary tail coefficients collapse under asymptotic independence, rendering them blind to subasymptotic concentration. In this paper, we introduce a unified framework of Spearman-like, tail-sensitive indices constructed via the ranks and concomitants of the data to assess localized association conditional on large threshold exceedances. We establish two complementary families of measures: a discrete two-parameter family that encompasses Spearman's $\rho$ as a special case, and a continuous single-parameter family obtained as its asymptotic limit. This threshold-defined framework offers a flexible, interpretable diagnostic tool that continuously tracks tail-association paths and successfully discriminates among fundamentally distinct subasymptotic structures where classical boundary indicators vanish. For both families, we investigate their theoretical properties - including their limiting behavior at the absolute boundary - propose empirical plug-in estimators, and derive their asymptotic distributions. The operational advantages of the indices are verified through analytical illustrations across diverse copula families and demonstrated via an empirical application to global catastrophic risk. 25 settembre 2026 ore 14 Sara Biagini, Department of AI, Data and Decision Sciences, LUISS University, Rome Title: An introduction to carbon markets regulation: carbon neutrality and Net-Zero Abstract: After introducing carbon markets, we analyze the impact of carbon dioxide regulation on a system of polluting, heterogeneous companies. We consider two compliance frameworks: one based on an emission trading system (ETS) mechanism and the other relying only on abatement efforts. The shocks in the economy are spanned by a multivariate Brownian motion, and the companies’ emissions are modeled as general diffusions. Firms must match their projected emission imbalance with their reduction effort at the compliance date in both frameworks. Under the ETS program, to do so firms can both abate and trade carbon permits in the ETS permits exchange. Existence and uniqueness of the optimal abatement and trade, together with the equilibrium carbon price, are proven under mild necessary and sufficient conditions. The optimizers and the carbon price are explicit, and their analytic expressions provide an instance of classic economic principles. Numerical examples illustrate the flexibility of the model in the study of the effect of significant allocation policies. Under the net-zero framework, firms can only rely on abatement, which is also provided in closed-form. Seguiranno, per ciascun seminario, le istruzioni per partecipare. Cordiali saluti dagli organizzatori: Giulio Bottazzi, Alessandro Calvia, Marco Capaldo, Enrico Scalas

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SEMINARIO presso Politecnico di Milano - 10.07.26 ore 11:30 - Hedayat Fathi
by Laura Maria Sangalli 29 Jun '26

29 Jun '26

Cari Colleghi, A seguire annuncio di un seminario organizzato presso il Laboratorio MOX - Politecnico di Milano Hedayat Fathi, Université Laval, Québec 10.07.26 ore 11:30 – Aula Saleri Link: https://mox.polimi.it/mox-colloquia-seminars-list/mox-seminars/?id_evento=2… Titolo: SOFIA and MIP-FoSR: Two Methods for Variable Selection in Functional Linear Regression Abstract: This presentation covers two recent contributions to variable selection in functional linear regression. For the scalar-on-function setting, we propose SOFIA (Scalar-On-Function Integrated Adaptive Lasso). We assume the functional covariates are in a Hilbert space while the coefficient functions belong to a specific subspace of it, such as a reproducing kernel Hilbert space. In this way, we impose a controlled level of smoothness or periodicity on the coefficients. The method satisfies a functional oracle property even when the number of predictors exceeds the sample size. For the function-on-scalar setting, we propose MIP-FoSR, a mixed-integer programming framework that performs simultaneous variable selection and outlier detection. It extends the "mean-shift outlier model" to the functional setting, and uses grouped binary indicators on basis-expansion coefficients to impose explicit bounds on the number of selected predictors and detected outliers. We establish an equivalence with a functional sparse trimming problem, derive a finite-sample breakdown point, and prove a functional robust strong oracle property. Un caro saluto a tutti, Laura Sangalli —— Laura Maria Sangalli MOX - Dipartimento di Matematica Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano - Italy (+39) 02 2399 4554 laura.sangalli(a)polimi.it https://sangalli.faculty.polimi.it

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SEMINARIO presso Politecnico di Milano - 02.07.26 ore 14:30 - M. Pegoraro
by Laura Maria Sangalli 29 Jun '26

29 Jun '26

Cari Colleghi, A seguire annuncio di un seminario organizzato presso il Laboratorio MOX - Politecnico di Milano Matteo Pegoraro, Università della Svizzera italiana 02.07.26 ore 14:30 – Aula Saleri Link: https://mox.polimi.it/mox-colloquia-seminars-list/mox-seminars/?id_evento=2… Titolo: Topological Data Analysis: Invariance Properties, Statistical Problems, and Topological Machine Learning Abstract: I will present some of my contributions to Topological Data Analysis through the problem of building rigorous and usable TDA pipelines. Starting from a function, mesh, or point cloud, one builds a filtration and extracts a topological summary, such as a persistence diagram, merge tree, or Reeb graph. I will discuss how these summaries encode coordinate-free and invariant information, and why turning this idea into a robust mathematical pipeline requires carefully designed metrics, stability results, and estimation procedures, using tools from topology, geometry, statistics, and optimal transport. This perspective also exposes a second difficulty: even once stable summaries have been constructed, many of them naturally live in non-linear metric spaces, making standard statistical and machine-learning methods difficult to apply directly. I will therefore conclude with recent work on Persistence Spheres, an explicit Hilbert-space embedding of persistence diagrams with provable bi-continuity, aimed at making topological summaries compatible with modern machine-learning pipelines. Un caro saluto a tutti, Laura Sangalli —— Laura Maria Sangalli MOX - Dipartimento di Matematica Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano - Italy (+39) 02 2399 4554 laura.sangalli(a)polimi.it https://sangalli.faculty.polimi.it

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Posizione RTT Trieste
by ASCI CLAUDIO 26 Jun '26

26 Jun '26

Cari colleghi, è aperta la selezione per il reclutamento di sei ricercatori a tempo determinato, ai sensi dell’art. 24 della L. n. 2402010 (RTT), per diversi SSD, tra cui MATH-03B (Probabilità e statistica matematica), presso il Dipartimento di Matematica, Informatica e Geoscienze, dell'Università degli Studi di Trieste. Il termine ultimo per la presentazione della domanda è il 20 luglio 2026. In allegato il bando. Saluti. Claudio Asci

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Registration open: Vienna-Copenhagen Conference on Financial Econometrics 2026
by Viktoria Schildhammer 26 Jun '26

26 Jun '26

Dear colleagues, Registration for the Vienna-Copenhagen Conference on Financial Econometrics 2026, taking place at the University of Vienna, Austria, from August 13–15, 2026, is now open. The conference brings together researchers working on theoretical, methodological, and empirical aspects of financial econometrics, statistics, applied mathematics, and quantitative economics. Topics of interest include, but are not limited to, risk measurement and management, asset pricing, financial forecasting, high-frequency statistics, market microstructure, derivatives, and machine learning. The conference features keynote lectures, parallel sessions, and poster presentations. Registration is open until July 26, 2026. For registration and further information, please visit: https://vieco2026.univie.ac.at We look forward to welcoming you to Vienna. Best regards, The Organizers

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Mini-mini course Alberto Bietti at Tor Vergata, June 30
by Michele Salvi 23 Jun '26

23 Jun '26

Dear all, It is not time to go to the seaside yet! On Tuesday, June 30th, at 14h00 in Aula Dal Passo in the Math Department of the University of Rome Tor Vergata, RoMaDS will host Alberto Bietti (Flatiron Institute, NYC), with the mini-mini-course (about 3 hours long) “Learning in Transformers with Associative Memories” Abstract: Large language models based on transformers have achieved great empirical successes. However, as they are deployed more widely, there is a growing need to better understand their internal mechanisms in order to make them more reliable. These models appear to store vast amounts of knowledge from their training data, and to adapt quickly to new information provided in their context or prompt. Through toy tasks for reasoning and factual recall, we highlight the role of weight matrices as associative memories, and provide theoretical results on how gradients enable their learning during training, how over-parameterization affects their storage capacity, and sample complexity. We encourage in-person partecipation. Should you be unable to come, here is the link to the Teams streaming: https://teams.microsoft.com/meet/366597487320635?p=lk1ffPDon4Quh9ygMt The seminar is part of the Excellence Project MatMod@TOV.

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