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Gruppo di studio: Dottorato in Probabilità e Statistica e Industria
by Enrico Scalas 01 Apr '25

01 Apr '25

Gruppo di studio: Dottorato in Probabilità e Statistica e Industria (“PhD Students in Probability and Statistics meet Companies”) Il gruppo UMI-PRISMA, il Dipartimento di Scienze Matematiche "G.L. Lagrange” del Politecnico di Torino e il Dipartimento di Matematica “G. Peano” dell’Università di Torino organizzano a Torino una tre giorni dal 16 al 18 settembre 2025 usando il formato ridotto dello "Study Group Mathematics with Industry": il mattino del 16 settembre, le aziende partecipanti presentano i problemi di loro interesse. Successivamente si formano gruppi di dottorandi supportati da tutor accademici, che lavorano su tali problemi e le soluzioni proposte sono discusse nel pomeriggio del 18 settembre. Al momento hanno già accettato di partecipare le seguenti società: Novartis (https://www.novartis.com/it-it/) ToolsGroup (https://www.toolsgroup.com/) La partecipazione al gruppo di studio è gratuita per dottorandi e dottorande che stanno svolgendo una tesi di probabilità e/o statistica matematica. Inoltre sarà disponibile un piccolo supporto finanziario su richiesta. Il supporto sarà erogato con un criterio di priorità per ordine di arrivo delle richieste. Infine, sarà rilasciato un certificato di partecipazione. In questa fase chiediamo una dichiarazione di interesse a partecipare. La si può inviare a: laura.sacerdote(a)unito.it prima possibile e comunque entro il 30 maggio 2025. Il comitato organizzatore: Gianluca Guadagni, Franco Pellerey, Laura Lea Sacerdote, Enrico Scalas, Serena Spina, Barbara Trivellato e Cristina Zucca

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Seminar Alexandra Holzinger - Luiss
by Marta Leocata 01 Apr '25

01 Apr '25

Dear all, The Department of Economics and Finance at Luiss University in Rome (https://economiaefinanza.luiss.it <https://economiaefinanza.luiss.it/>) is pleased to announce the following seminar: Speaker: Alexandra Holzinger, Mathematical Institute, University of Oxford Title: Fluctuations around the mean-field limit for attractive Riesz interaction kernels in the moderate regime When: April 3, 14:30 Where: Viale Romania, 32 00197 Rome Meeting room: 405 Abstract: In this talk I will give a short introduction to moderately interacting particle systems and the general notion of fluctuations around the mean-field limit. We will see how a central limit theorem can be shown for moderately interacting particles on the whole space for certain types of interaction potentials. The interaction potential approximates singular attractive potentials of sub-Coulomb type and we can show that the fluctuations become asymptotically Gaussians. The methodology is inspired by the classical work of Oelschläger in the 1980s on fluctuations for the porous-medium equation. To allow for attractive potentials we use a new approach of quantitative mean-field convergence in probability in order to include aggregation effects. Should you be interested, please kindly send me an e-mail. Best wishes, Marta Leocata

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Announcement of the summer school "Mathematical methods for high-dimensional data", 8-12 September 2025
by Alberto Fachechi 01 Apr '25

01 Apr '25

Dear Colleagues, We are glad to announce the summer school Mathematical methods for high-dimensional data <https://sites.google.com/view/math-high-dimensional-data/home>, which will take place on September 8-12, 2025, at the Mathematics Department of Sapienza University of Rome. Lecturers of the school are Jean Barbier (International Centre for Theoretical Physics) Marylou Gabrié (École Normale Supérieure) Alessandro Ingrosso (Radboud University) Silvia Villa (University of Genova) The school will also include poster sessions for PhD students and early postdocs. To register, please complete the form available on the website (here the link <https://sites.google.com/view/math-high-dimensional-data/registration?authu…>). Participation is free, but registration is mandatory. The school will launch the Eccellenza Scientific Program dedicated to Data Science, running through January 2026. This program features workshops, doctoral courses, and seminar series, focusing on the mathematical methods underpinning data science. Participants will engage with cutting-edge methodologies in statistical physics, statistical inference, optimization, and control, alongside advanced techniques in numerical simulations and scientific computing for machine learning. By integrating these disciplines, the program provides an overview of rigorous foundations and tools for tackling real-world challenges through data-driven approaches. More about the program will be found on this page <https://sites.google.com/view/math-high-dimensional-data/home>. For additional information, do not hesitate to contact us. Best regards, The organisers of the school Elena Agliari Emanuele Caglioti Alberto Fachechi Lorenzo Taggi -- Alberto Fachechi, PhD Researcher (RTD-A) Dipartimento di Matematica G. Castelnuovo Sapienza Università di Roma

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Reminder: A Spring Day in Probability and Statistical Physics - 11 April 2025, Florence
by Gianmarco Bet 01 Apr '25

01 Apr '25

Dear colleagues, This is a reminder that on Friday, *April 11th*, the fifteenth seminar day in the “Days in Probability and Statistical Physics” will take place.in at the Department of Mathematics and Computer Science "Ulisse Dini", Viale Morgagni 67/a, Florence. Lecturers: Prof. *Clara Stegehuis* (Twente University) Title: Detecting geometry in scale free networks Prof.* David Belius* (UniDistance Suisse) Title (Introductory lecture): The story of mean-field spin glasses Title (Seminar): The Thouless-Andersson-Palmer (TAP) approach to mean-field spin glasses Each speaker will give a 45 minutes introductory lecture tailored for non-experts, followed by another 45 minutes of seminar-style presentation (see program). More information, including the abstracts, can be found on the event’s webpage <https://sites.google.com/unifi.it/florence-probability-group/probability-da…> . *Practical notes*: for organization purposes, we kindly ask those who plan to attend to fill out the following Google Form *by* *April 6*: https://forms.gle/zYv2BFAmMy42cf8y8 We look forward to seeing many of you and please feel free to share the announcement with those you think may be interested, particularly to young researchers! Luca Avena, Luisa Andreis, Gianmarco Bet and Elia Bisi Scientific advisory committee: F. Caravenna, E.N.M. Cirillo, F. Colomo, P. Dai Pra, A. De Masi, C. Giardina`, R. Livi, F. Martinelli, I.G. Minelli, B. Scoppola, E. Scoppola. *PROGRAM* 10:30-11:00 Welcome coffee 11:00-11:45 Introductory lecture: Stegehuis 11:45-12:15 Break 12:15-13:00 Seminar: Stegehuis 13:00-14:30 Lunch 14:30-15:15 Introductory lecture: Belius 15:15-15:45 Break 15:45-16:30 Seminar: Belius You can find here <https://mail.google.com/mail/u/1/#search/probability+day+11+aprile/FMfcgzQZ…> the poster of the event.

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Seminars in Statistics at Collegio Carlo Alberto - Sergios AGAPIOU (University of Cyprus)
by Matteo Giordano 28 Mar '25

28 Mar '25

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.google.com/url?q=https://www.carloalberto.org/events/category/s…> Venerdì 04/04/2025, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ 12.00-13.00 Speaker: Sergios AGAPIOU (University of Cyprus) Title: HEAVY-TAILED BAYESIAN NONPARAMETRIC ADAPTATION OVER BESOV SPACES Abstract: We will consider the Bayesian recovery of an unknown function from direct observations polluted by white Gaussian noise, and we will be interested in studying the asymptotic performance of the posterior in the infinitely informative data limit, in terms of rates of contraction. We will be especially interested in priors which are adaptive to the smoothness of the unknown function. In the past decade, certain hierarchical and empirical Bayes procedures based on Gaussian process priors, have been shown to achieve adaptation to spatially homogenous smoothness. However, we have recently shown that Gaussian priors are suboptimal for spatially inhomogeneous unknowns, that is, functions which are smooth in some areas and rough or even discontinuous in other areas of their domain. Such unknowns are abundant in applications such as imaging, and can be modeled using Besov spaces, which generalize (the more widely known) Sobolev and Hölder spaces. In contrast to Gaussian priors, we have shown that (similar) hierarchical and empirical Bayes procedures based on Laplace (series) priors, achieve adaptation to both homogeneously and inhomogeneously smooth functions. All of these procedures involve the tuning of a hyperparameter of the Gaussian or Laplace prior. We will introduce Besov spaces and will recall their minimax theory developed in the mid-late 90’s and has various interesting features. After reviewing the above Bayesian results, we will present a new strategy for adaptation to smoothness based on heavy-tailed priors. Specifically, we will show that adaptive rates of contraction in the minimax sense (up to logarithmic factors) are achieved without tuning of any hyperparameters. This adaptation is achieved for both homogeneously and inhomogeneously smooth unknowns, in particular, we will show that the studied heavy-tailed priors are adaptive over all Besov spaces and for all L^p-losses, for p from 1 up to infinity. Extensive numerical simulations corroborating the theory will be presented as well. This is joint work with Masoumeh Dashti, Tapio Helin, Aimilia Savva and Sven Wang (Laplace priors), and Ismaël Castillo and Paul Egels (heavy-tailed priors) ------------------------------------------------ Sarà possibile il seminario anche in streaming: chiunque volesse collegarsi è pregato di inviare una email entro *mercoledì 02/04/2025* a matteo.giordano(a)unito.it <mailto:matteo.giordano@unito.it> . Il webinar è organizzato dalla "de Castro" Statistics Initiative (www.carloalberto.org/stats <http://www.carloalberto.org/stats>) in collaborazione con il Collegio Carlo Alberto. Cordiali saluti, Matteo Giordano Assistant Professor (RTDA) Department of Economics, Social Studies, Applied Mathematics and Statistics (ESOMAS) www.matteogiordano.weebly.com <https://matteogiordano.weebly.com/>

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Associate Professor in Probabilistic Machine Learning in Oslo ?
by Arnoldo Frigessi 28 Mar '25

28 Mar '25

Want to be Associate Professor in Probabilistic Machine Learning in the Oslo Centre for Biostatistics and Epidemiology and Integreat, the Norwegian centre for Knowledge-driven Machine Learning, University of Oslo, Norway? Permanent position. Application deadline: May 18, 2025 Location: University of Oslo, Oslo, Norway Start date: To be agreed upon. Join us in shaping the future of Probabilistic Machine Learning in a vibrant international research community! Find out more: https://www.jobbnorge.no/en/available-jobs/job/276924/associate-professor-a… Apply now: https://www.jobbnorge.no/en/available-jobs/job/276924/associate-professor-a… More information: Integreat: https://www.integreat.no/ Oslo Centre for Biostatistics and Epidemiology: https://www.med.uio.no/imb/english/research/centres/ocbe/ University of Oslo International Office: https://www.uio.no/english/about/vacancies/ismo/ Contact us for a chat: Arnoldo Frigessi: frigessi(a)uio.no<mailto:frigessi@uio.no> Manuela Zucknick: manuela.zucknick(a)medisin.uio.no<mailto:manuela.zucknick@medisin.uio.no> Welcome to Norway, where we build trustworthy AI together.

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MOX COLLOQUIUM - 10.04.25 ore 14:30 – Mihaela van der Schaar
by Laura Maria Sangalli 27 Mar '25

27 Mar '25

Cari Colleghi, vi segnalo il seguente seminario, in modalità ibrida, della serie dei MOX COLLOQUIA: 10.04.25 Ore 14:30 - Aula IV, Edificio 11, Politecnico di Milano Speaker: Mihaela van der Schaar, Faculty of Mathematics, University of Cambridge Titolo: Can we discover fundamental laws from data using AI? Abstract: Discovering fundamental laws governing systems from observational data has long been a hallmark of scientific inquiry. In this talk, I will discuss how recent advances in AI and machine learning enable the automated discovery of scientific laws and governing equations directly from data, revolutionizing the way we unravel system dynamics in numerous domains, including medicine and pharmacology. I will highlight how AI-driven methods uncover underlying principles, from classical physics to biological systems to medicine, and offer insights into future possibilities—transforming data-driven observations into interpretable and actionable scientific knowledge. Yet, can we push this boundary further—going beyond equations entirely? I will introduce direct semantic modeling, a novel paradigm where AI learns the behavior of dynamical systems directly from data without relying on closed-form equations. This semantic approach offers intuitive, human-interpretable insights into system evolution, marking a transformative leap in scientific discovery. (This talk is based on recent research with Krzysztof Kacprzyk, Tennison Liu and Sam Holt.) Il seminario sarà accessibile online: https://mox.polimi.it/mox-colloquia-seminars-list/mox-seminars/?id_evento=2… https://cassyni.com/events/SAFbogPTLoJ6dkTvUoNtWy Seguirà rinfresco. Cari saluti, 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<mailto:laura.sangalli@polimi.it> https://sangalli.faculty.polimi.it

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I: Open PhD Positions at TU Delft in Probability, Geometry, PDEs, and Optimal Transport
by Francesca Collet 27 Mar '25

27 Mar '25

Ricevo ed inoltro. Cordiali saluti, Francesca Collet ________________________________ Da: Richard Kraaij <R.C.Kraaij(a)tudelft.nl> Inviato: giovedì 27 marzo 2025 16:05 A: Francesca Collet <francesca.collet(a)univr.it> Oggetto: Open PhD Positions at TU Delft in Probability, Geometry, PDEs, and Optimal Transport Dear colleagues, The TU Delft Applied Probability section has three open PhD positions in the area where probability theory intersects with geometry, PDEs, and optimal transport. https://careers.tudelft.nl/job/Delft-PhD-Position-in-Probability-Theory-and… – Application deadline: April 6 https://careers.tudelft.nl/job/Delft-PhD-Position-in-Probabilty-Theory-and-… – Two positions available, application deadline: April 27 If you know anyone who might be interested, we would greatly appreciate it if you could share this opportunity within your networks and with potential candidates. Best regards, Rik Versendaal & Richard Kraaij

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Fwd: The 10th BSDE Conference in 2025
by Gianmario Tessitore - UNIMIB 27 Mar '25

27 Mar '25

Diffondo molto volentieri Dear Colleagues, We are pleased to announce that the website for *the 10th conference on BSDEs to be held in Shandong University, Qingdao, P.R. China, from June 26 to July 1, 2025*, is now ready: https://bsde2025.conferencesvc.com/ Here, you may find: - Key dates & submission guidelines - Registration details - Information on organizing sessions - Updates on invited speakers (The list of confirmed **invited speakers** will be updated on the website by the end of this month) **Call for Participation:** We warmly encourage you to: ✔ Submit proposals. ✔ Register early to secure your spot. Best regards, Juan Li Shandong University, Weihai & Qingdao On behalf of the local organizers. -- Gianmario Tessitore Dipartimento di Matematica e Applicazioni Università degli Studi di Milano-Bicocca

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QFinLab Seminar - Claudio Fontana (Università di Padova) - 2/4/2025, 12:15 @ Department of Mathematics, Politecnico di Milano
by Alessandro Calvia 27 Mar '25

27 Mar '25

Dear colleagues, you are all invited to participate in the following seminar organized by QFinLab - Department of Mathematics, Politecnico di Milano. Wednesday, 2 April 2025, 12.15-13.15 Seminar room, third floor, building 14, Via Bonardi 9, Milano (Leonardo Campus) Claudio Fontana (Università di Padova) Title: A stochastic Gordon-Loeb model for optimal security investment under clustered cyber-attacks. Abstract: We propose a continuous-time extension of the Gordon-Loeb model for optimal investment in information security under the threat of cyber-attacks. The arrival of attacks is modeled using Hawkes processes, capturing the realistic feature of clustering in cyber-attacks. Each attack may lead to a system breach, with the probability of breach depending on the system's vulnerability. We aim at determining the optimal investment in cyber-security to reduce the system's vulnerability. The problem is formulated as a two-dimensional Markovian stochastic control problem and solved via dynamic programming techniques. We perform a numerical study of the value function and the associated optimal investment strategy in cyber-security, highlighting the impact of randomly arriving clustered cyber-attacks. Based on a joint work with G. Callegaro, C. Hillairet, B. Ongarato. Next seminar: Alessandro Sbuelz (Università Cattolica del Sacro Cuore), 7 May 12.15. All news can be found on the QFinLab webpage<https://www.qfinlab.polimi.it/seminars-and-meetings/>. The organizers: Michele Azzone and Alessandro Calvia.

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