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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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Mini-courses in GSSI trimester
by Lu Xu 31 Mar '25

31 Mar '25

Dear colleagues and friends, as part of the GSSI intensive trimester “Particles, Fluids and Patterns: analytical and computational challenges”, we are glad to announce 3 short courses in April: April 14-17: Prof. Makiko Sasada (Tokyo) April 28-30: Prof. Oriane Blondel (Lyon) and Prof. Alessandro Giuliani (Rome) Please see at the end of the email for the detailed place and time, titles and abstracts. Other courses hosted by the trimester can be found in https://trimester2025.math.gssi.it/all_courses/. Registration is free through the web form: https://indico.gssi.it/event/745/. We would be grateful if you could circulate the announcement among potentially interested students and researchers. For any information do not hesitate to contact us (patterns(a)gssi.it). ———————————————— Venue for all courses: Main Lecture Hall, Gran Sasso Science Institute (Viale F. Crispi 7, L’Aquila) ———————————————— Introduction to probabilistic aspects of integrable systems Lecturer: Makiko Sasada (The University of Tokyo) 14/4 (Mon) 9:00-10:30 15/4 (Tue) 14:15-15:45 16/4 (Wed) 10:45-12:15 17/4 (Thu) 9:00-10:30 In recent years, there has been growing interest in the study of integrable systems from the perspectives of statistical mechanics and probability theory. The theory of generalized hydrodynamics, developed by mathematical physicists, suggests that the macroscopic behavior of integrable systems is highly universal. To mathematically substantiate such theories with concrete models, a type of cellular automaton called the box-ball system (BBS) has been extensively studied by probabilists in recent years. The BBS, which exhibits solitonic behavior, has been studied from various viewpoints, such as tropical geometry, combinatorics, and representation theory, over 30 years. However, research from the probabilistic perspective began only about 10 years ago. Recently, probabilistic approaches, including the application of the Pitman transform, analysis of invariant measures, and scaling limits, have rapidly expanded. These have revealed new connections between probability theory and classical integrable systems, showing that the macroscopic behavior of integrable systems exhibits a universality distinct from that of chaotic systems. In this lecture, I will introduce these new research topics, mainly focusing on the box-ball system, and present the rigorous results obtained in the past several years, starting from the basic concepts. ———————————————— Long range order in atomistic models for solids Lecturer: Alessandro Giuliani (Rome Tre) 28/4 (Mon) 16:15-17:45 29/4 (Tue) 16:15-17:45 30/4 (Wed) 10:45-12:15 & 14:15-15:45 The emergence of long range order at low temperatures in atomistic systems with continuous symmetry is a fundamental, yet poorly understood phenomenon in physics. To address this challenge I will introduce a discrete microscopic model for an elastic crystal with dislocations in three dimensions, originally proposed by Ariza and Ortiz. The model is rich enough to support some realistic features of three-dimensional dislocation theory, most notably grains and the Read-Shockley law for grain boundaries, which I will review and show how to derive microscopically in the context of the Ariza-Ortiz model, at least in a simple, explicit geometry. I will also explain how to analyze the model at positive temperatures, in terms of a Gibbs distribution with energy function given by the Ariza–Ortiz Hamiltonian plus a contribution from the dislocation cores. The main result is that the model exhibits Long Range Positional Order (LRPO) at low temperatures. Its proof is based on the tools of discrete exterior calculus, together with cluster expansion techniques. In this mini-course I will introduce these methods and explain how to combine them in order to prove existence of LRPO. Time permitting, I will discuss some perspectives about the extension of these ideas and methods to two dimensions. Based on joint work with Florian Theil. ———————————————— Fluctuations in exclusion processes Lecturer: Oriane Blondel (University of Lyon 1) 28/4 (Mon) 10:45-12:15 29/4 (Tue) 9:00-10:30 & 14:15-15:45 30/4 (Wed) 16:15-17:45 We will focus on weakly asymmetric exclusion processes on the line or half-line, and investigate their fluctuations out of equilibrium. We will review the various tools used in proving convergence to the KPZ equation in the strategy initiated in [Bertini-Giacomin ‘97] and discuss how they can be adapted to the singular initial condition that arises when one considers fluctuations of the facilitated exclusion process at the interface. ———————————————— With our best wishes, Lu Xu Assistant Professor (RTDb) Gran Sasso Science Institute

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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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Stat Learning position in Luxembourg
by Giovanni Peccati 26 Mar '25

26 Mar '25

Dear Colleagues, A new position (Assistant/Associate level) in *Statistical Learning *is open at the *Department of Mathematics of Luxembourg University (DMATH)*. Deadline for applications; *June 30th, 2025* Here is a link to the official announcement: http://emea3.mrted.ly/3uk09 With kind regards, Giovanni Peccati -- Prof. Giovanni Peccati ------------------------------------------ Head of the Department of Mathematics Faculty of Science, Technology and Medicine ------------------------------------------ University of Luxembourg ------------------------------------------ President of the Luxembourg Mathematical Society https://math.uni.lu/sml/ ------------------------------------------ homepage: http://sites.google.com/site/giovannipeccati/home E-mail: giovanni.peccati(a)gmail.com

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