January 2026 - Random - Mailing list — Dipartimento di Matematica, UniPI

summer School on PDEs and Randomness in Leipzig, July 2026
by b4buu7＠gmail.com 29 Jan '26

29 Jan '26

Dear all, this is to announce that at MPI in Leipzig the second edition of the summer school on ''PDE and Randomness'' will take place from the 13th to the 17th of July this year (2026), more information at the following link: https://www.mis.mpg.de/events/series/2nd-summer-school-on-pdes-and-randomne… In this second edition of the summer school on PDEs and Randomness, three speakers will present introductions to their areas of research at the interface of PDEs and probability: Yu Gu (University of Maryland) Lisa Hartung (Universität Mainz) Hendrik Weber (Universität Münster) Additionally, there will be tutorial sessions organized by the junior participants with support from the organizers. Funding towards travel and accommodation is available for early-career participants such as postdoctoral researchers, PhD and master students. Deadline for funding applications is February 28, 2026. Please note that the funding deadline is approaching and there are still some free slots for getting financial support. Kind regards, Francesco.

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Short course at IMT Lucca
by Irene Crimaldi 29 Jan '26

29 Jan '26

Dear all, I would like to bring to your attention the short course "Advanced Topics in Stochastic Modeling and Statistics" (12 hours). I will teach this course in person at IMT Lucca https://www.imtlucca.it/homepage, but it is also possible to attend it online. The course is divided into six lessons in the period April 16-27 2026. The course deals with the following topics: - Conditional expectation (definition, properties); - Martingales and co. (definitions and basic properties, Burkholder transform, stopping theorem and some applications, predictable compensator and Doob decomposition, some convergence results, game theory interpretation, variants); - Introduction to stochastic processes with reinforcement (definition, applications, classical models, recent models, including models with interaction, related statistical tools, ongoing research). Participation in the course is free. Registration as a visiting student is required, following the instructions at https://www.imtlucca.it/corsi-visiting-students Once registered, the class schedule will be provided. Interested students can contact me for further details Best, Irene Crimaldi

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Open Ph.D. position at the University of Luxembourg
by Giovanni Peccati 27 Jan '26

27 Jan '26

Dear Colleagues, The *Department of Mathematics* of the *University of Luxembourg* (*DMATH*) is seeking an excellent candidate for a *PhD position* in the area of *Mathematical Statistics*, with an expected starting date in *2026*. *-----------------------* *Supervisor:* Prof. *Yannick Baraud* (https://math.uni.lu/baraud/Home.html) *PhD topic:* *Classical Bayesian methods can be used to construct estimators with good statistical properties. For example, when the data are i.i.d. and come from a distribution belonging to a parameterised model with a suitable prior distribution, numerous studies show that the posterior distribution is concentrated around the parameter associated with the distribution of the data.* *Despite their popularity, these methods nevertheless have certain limitations. In particular, when the data-generating distribution does not belong to the family of distributions chosen as the model, the estimators obtained may be of poor quality, even when the model provides a good approximation of the truth. This situation can arise, for example, when the sample contains a few outliers due to measurement or transcription errors. More generally, it occurs when the statistical model is only a simplification of reality, which is often the case in practice. The statistical method is then said to suffer from a lack of robustness as it produces unstable estimators that are sensitive to small deviations from the assumed model.* *In this PhD proposal, we offer the opportunity to study a robust alternative to classical Bayesian methods. This is a recent approach, the main properties of which were established in [1] in the context of density estimation. The aim of this PhD proposal is to understand the mathematics behind these new techniques and to extend it beyond density estimation. * *A candidate for this position must have a strong background in analysis, probability and mathematical statistics as well as a taste for theory. * [1] Y. Baraud. From robust tests to Bayes-like posterior distributions. Probab. Theory Related Fields, 188(1-2):159–234, 2024. --------------------------- The successful candidate will join a dynamic research environment with strong international collaborations and access to high-level scientific infrastructure. For further details concerning the position, application procedure, and eligibility requirements, please contact directly Prof. Baraud at the address yannick.baraud(a)uni.lu Please feel free to circulate this announcement within your networks. Best 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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seminar Claudio Macci 30/01/26 - Pavia
by Enrico Priola 26 Jan '26

26 Jan '26

Dear Colleagues, We would like to invite you to the following seminar, by Claudio Macci on Friday 30 january 2026, starting at 11 am. Titles and abstract are below. With best regards, Enrico Priola ---- Friday 30 january 2026 at 11 am - Aula Beltrami, via Ferrata 5, Università di Pavia Link Zoom https://unipv-it.zoom.us/j/95012043373?pwd=VaSaGaIDZQnbVWixaqeDzI4uhY5H2I.1 ID riunione: 950 1204 3373 Codice d’accesso: 789010 Speaker: Claudio Macci (Università di Roma Tor Vergata) TITLE Some recent large deviation results on random neural networks ABSTRACT In this talk, I consider random neural networks with Gaussian weights and biases. A well-known result (proved under various assumptions in several references) concerns the convergence in distribution of the network output, in the infinite-width limit, to a centered Gaussian process with i.i.d. components (with the depth $L$ kept fixed). I will present some large deviation results describing a collapse of the network output (which, as expected, converges to the zero vector) when it is multiplied by a scaling factor tending to zero; see [1], where moderate deviations are also studied. In the final part, I will briefly outline some results in a very recent work (see [2]) concerning the deep limit (that is, as $L\to\infty$) for a generic component of the Gaussian process mentioned above. REFERENCES [1] C. Macci, B. Pacchiarotti, G.L. Torrisi. Journal of Applied Probability (2026), in press. [2] S. Di Lillo, C. Macci, B. Pacchiarotti. Submitted, and available on arxiv. -- Enrico Priola Dipartimento di Matematica, Università di Pavia Via Adolfo Ferrata 5, 27100 Pavia tel +39 0382 985639

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LinStat 2026
by Elvira Di Nardo 26 Jan '26

26 Jan '26

International Conference on Trends and Perspectives in Linear Statistical Inference August 24–28, 2026, Poznań University of Technology, Poznań, Poland This is to announce LinStat 2026, an international conference bringing together researchers interested in statistics and its applications, as well as matrix analysis and its use in statistics. The meeting will provide an opportunity to discuss current developments in linear statistical inference and related fields. The conference programme will include plenary lectures and a series of thematic sessions covering linear modelling methods, estimation, testing, and prediction in economic, medical, and social science data; multivariate and high-dimensional data analysis with complex data structures; robustness of statistical methods; variance component estimation in linear and generalized models; design and analysis of experiments; and applications of matrix methods in statistics. Special attention will be given to young scientists. Awards for the best poster and the best talk will be presented to graduate students or researchers with a recently completed Ph.D., and the prize-winning contributions will be promoted by the conference. Plenary Speakers: Syed Ejaz Ahmed (Brock University, Canada) Małgorzata Bogdan (University of Wrocław, Poland) Elvira Di Nardo (University of Turin, Italy) Werner G. Müller (Johannes Kepler University Linz, Austria) Thomas Mathew (University of Maryland Baltimore County, USA) Jianfeng Yao (The Chinese University of Hong Kong, Shenzhen, China) Further information is available at https://linstat2026.put.poznan.pl/ <https://linstat2026.put.poznan.pl/?utm_source=chatgpt.com> -- %------------------------------------------------------- Elvira Di Nardo Dept. Mathematics "G. Peano" University of Torino Via Carlo Alberto 10 10123 Torino, Italia tel. +39 0116702862 fax +39 0116702878 www.elviradinardo.it *https://sites.google.com/view/elviradinardo <https://sites.google.com/view/elviradinardo>* %-------------------------------------------------------

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Postdoc in Luxembourg
by Giovanni Peccati 23 Jan '26

23 Jan '26

Dear Colleagues, A 3-year post-doc position is open in my group, with a general focus on stochastic analysis. The earliest possible starting date is May 1st, 2026. Applications should be sent through the webpage below, which also contains more information: http://emea3.mrted.ly/43wi6 With my best 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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BioInference2026 at St Andrews - Scotland!
by Massimiliano Tamborrino 23 Jan '26

23 Jan '26

Dear all, We are thrilled to announce that BioInference2026 is going to St Andrews, Scotland, from the 10th to the 12th of June, 2026! BioInference brings together researchers from statistics and mathematical modelling who work on biological systems, creating a lively space for exchanging ideas, sparking collaborations, and building community across all career stages. After last year’s successful three-day meeting in Bardonecchia, we’re excited to return with another three days packed with invited and contributed talks, poster sessions, and dedicated networking opportunities. ________________________________ Call for Abstracts We now invite submissions for oral or poster presentations on any work involving mathematical modelling, statistical methods, or machine learning approaches for broadly interpreted biological problems. All presentations will be in person with no parallel sessions. Abstract deadline: 31 January 2026 Submit here: Abstract Submission Link<https://docs.google.com/forms/d/e/1FAIpQLSc8VlIsRWPs3acc1lkOw4Uap0IWmKVSVaD…> ________________________________ Invited Speakers for 2026 We are delighted to host an exceptional line-up of invited speakers: * Marta Belchior Lopes<https://martabelchiorlopes.wixsite.com/website> (Universidade NOVA de Lisboa) * Sokratia Georgaka<https://research.manchester.ac.uk/en/persons/sokratia.georgaka> (University of Manchester) * Jochen Kursawe<https://www.st-andrews.ac.uk/mathematics-statistics/people/jk263/> (University of St’ Andrews) * Theo Kypraios<https://www.maths.nottingham.ac.uk/plp/pmztk/> (University of Nottingham) * Sara Wade<https://sarawade.owlstown.net/> (University of Edinburgh) * Michael Whitehouse<https://michael-whitehouse.github.io/> (Imperial College London) * Konstantinos Zygalakis<https://webhomes.maths.ed.ac.uk/~kzygalak/> (University of Edinburgh) ________________________________ Registration Registration for the conference will open in 2026. The registration fee (covering three lunches and all coffee breaks) is expected to be around £100. ________________________________ More Information Learn more about the conference, past talks and posters, and this year’s host town, St Andrews, at: https://bioinference.github.io/2026/ If you have any questions, feel free to contact us at bioinference(a)gmail.com<mailto:http://bioinference@gmail.com>. Kind regards, Massimiliano on behalf of the 2026 BioInference Organisers ------ Dr. Massimiliano Tamborrino Reader (Associate Professor) and WIHEA Fellow Department of Statistics University of Warwick https://warwick.ac.uk/tamborrino

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Workshop Gnampa - 27 Gennaio - Luiss
by Marta Leocata 22 Jan '26

22 Jan '26

Cari colleghi, vi scrivo per comunicarvi che martedì 27 gennaio, presso la LUISS in Viale Romania 32, si terrà il workshop dal titolo “Mathematical Models for Climate Impacts”, che costituisce l’evento conclusivo del progetto GNAMPA “Mathematical methods for climate impacts: control, game theory, and inverse problems for EBCM”. In allegato trovate la locandina dell’evento. Per partecipare in presenza, o online, inviate una mail a mleocata(a)luiss.it <mailto:mleocata@luiss.it>. Marta

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LiBERA midterm workshop: Stochastic Dynamics, Interacting Particle Systems and Applications
by Stefano Pagliarani 21 Jan '26

21 Jan '26

Dear all, It is a pleasure to announce the LiBERA<https://site.unibo.it/libera/en> midterm workshop: International Workshop on Stochastic Dynamics, Interacting Particle Systems and Applications taking place 14th-19th June 2026 at Instituto Superior Técnico, Lisbon, Portugal The registration is open: https://sites.google.com/view/liberamidtermworkshop/home Title and abstract submission for short talks and posters is available until February 28th, 2026. Invited Speakers: Alekos Cecchin, University of Padova Maria Fernanda Cipriano, NOVA University Lisbon Ana Bela Cruzeiro, Instituto Superior Técnico Gonçalo dos Reis, University of Edinburgh Liliana Esquivel, University of Puerto Rico Noufel Frikha, Université Paris 1 Panthéon-Sorbonne Dario Gasbarra, University of Vaasa Erika Hausenblas, Montanuniversität Leoben (to be confirmed). Michael Högele, Universidad de Los Andes Mauricio Junca, Universidad de Los Andes Kush Kinra, NOVA School of Science and Technology Mateusz Majka, Heriot-Watt University Ester Mariucci, Laboratoire de Mathématiques de Versailles, Université de Versailles Saint-Quentin Leonard Monsaingeon, NOVA.Math NOVA FCT Maria João Oliveira, Universidade Aberta Stefano Pagliarani, University of Bologna Andrea Pascucci, University of Bologna Antonelle Pesce, University of Bologna Beatriz Salvador, Instituto Superior Técnico Günter Schütz, Instituto Superior Técnico Jonas Tölle, Aalto University Organizing committee Gerardo Barrera Vargas (CAMGSD, IST, Lisbon). Patrícia Gonçalves (CAMGSD, IST, Lisbon). Tiecheng Xu (CAMGSD, IST, Lisbon). LiBERA: https://site.unibo.it/libera/en

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[STAR Seminars] Wed Jan 21 - Susanna Dehò
by Leonardo Tarquini 21 Jan '26

21 Jan '26

Dear all, Join us for our upcoming talk in the STAR seminar<https://www.mn.uio.no/math/english/research/projects/storm/events/seminars/…> series on Wednesday, January 21st, from 11:00 to 12:00 (Oslo time). As always, the talk will take place in a hybrid format: participants in Oslo can attend the talk in Room 723 in Niels Henrik Abels hus, whereas the international audience will be able to follow the talk via Zoom<https://uio.zoom.us/j/67027975721>. The speaker is Susanna Dehò (University of Milano "La Statale") with the talk: Title: Symmetries of SDEs: from invariance properties to integration by parts formulas Abstract: The study of symmetries in differential equations, pioneered by Sophus Lie, constitutes a fundamental geometric approach to understand the invariance properties governing a dynamical system. By identifying the groups of transformations that preserve the equation’s structure, this framework provides systematic tools for order reduction, the construction of exact solutions, and the simplification of complex problems. Although symmetry analysis stands as a classical pillar for deterministic differential equations (ODEs and PDEs), supported by extensive literature, its extension to Stochastic Differential Equations (SDEs) represents a relatively recent field of research. Recent literature has also highlighted significant connections with the symmetries of the associated Fokker-Planck or Kolmogorov equations. Furthermore, the application of Lie symmetry theory to SDEs enables the derivation of integration by parts formulas inspired by Bismut’s variational approach to Malliavin calculus, with notable applications to the analysis of the law and regularity of the processes, as well as to the development of a stochastic calculus of variations. In this talk, we will discuss various notions of symmetry for SDEs, highlighting their connections to established invariance properties of well-known stochastic models and the symmetries of Kolmogorov PDEs. We will analyze how a geometric approach, inspired by Lie’s deterministic framework, enables the development of powerful computational tools for symmetry calculation. Subsequently, we will demonstrate how applying this geometric theory allows for the constructive derivation of an integration by parts formula for SDEs, rooted in Bismut’s approach. Finally, we will show how this integration by parts formula acts as a generating identity for well-known probability formulas, and discuss its connections to Stein’s identities. This contribution is based on a joint work with F.C. De Vecchi, P. Morando and S. Ugolini. Susanna Dehò, Francesco C. De Vecchi, Paola Morando, and Stefania Ugolini. Random rotational invariance of integration by parts formulas within a Bismut-type approach. Journal of Mathematical Physics: in print, 2025. We are looking forward to seeing you! Best regards, Giulia, Leonardo and Pere

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