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

Funded PhD Opportunity in Decentralized Finance at Dublin City University
by Paolo Guasoni 13 Apr '26

13 Apr '26

Expressions of interest are invited for a funded PhD position in Decentralized Finance at Dublin City University, beginning on 1 October 2026. The position offers a stipend of EUR 25,000 per year. Candidates should have strong training in mathematics, familiarity with programming, and a strong interest in decentralized finance. Interested candidates should send a CV, transcripts (undergraduate and above), and the names and email addresses of their referees to paolo.guasoni(a)dcu.ie by 30 April 2026. Successful candidates will be invited to an online interview by 15 May 2026. Best regards, Paolo Guasoni -- Séanadh Ríomhphoist / Email Disclaimer Tá an ríomhphost seo agus aon chomhad a sheoltar leis faoi rún agus is lena úsáid ag an seolaí agus sin amháin é. Tá cosc iomlán ar scaipeadh, dháileadh nó chóipeáil neamhúdaraithe ar an teachtaireacht seo agus ar aon cheangaltán atá ag dul leis. Má tá an ríomhphost seo faighte agat trí dhearmad cuir sin in iúl le do thoil don seoltóir agus scrios an teachtaireacht. D’fhéadfadh sé gurb iad tuairimí an údair agus sin amháin atá in aon tuairimí nó dearcthaí atá curtha i láthair sa ríomhphost seo agus níor chóir glacadh leo mar thuairimí nó dhearcthaí Ollscoil Chathair Bhaile Átha Cliath. Ní ghlactar leis go bhfuil cumarsáid ríomhphoist den sórt seo saor ó víreas, in am, slán, nó saor ó earráid agus ní ghlacann Ollscoil Chathair Bhaile Átha Cliath le dliteanas in aon chás den sórt sin ná as aon iarmhairt a d’eascródh astu. This e-mail and any files transmitted with it are confidential and are intended solely for use by the addressee. Any unauthorised dissemination, distribution or copying of this message and any attachments is strictly prohibited. If you have received this e-mail in error, please notify the sender and delete the message. Any views or opinions presented in this e-mail may solely be the views of the author and cannot be relied upon as being those of Dublin City University. E-mail communications such as this cannot be guaranteed to be virus-free, timely, secure or error-free and Dublin City University does not accept liability for any such matters or their consequences. -- <https://www.facebook.com/DCU/> <https://twitter.com/DCU> <https://www.linkedin.com/company/dublin-city-university> <https://www.instagram.com/dublincityuniversity/?hl=en> <https://www.youtube.com/user/DublinCityUniversity>

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Seminar Keles at Tor Vergata, April 20
by Michele Salvi 13 Apr '26

13 Apr '26

Dear all, On Monday, April 20th, at 14h00 in Aula Dal Passo in the Math Department of the University of Rome Tor Vergata, RoMaDS (https://www.mat.uniroma2.it/~rds/events.php) will host Ahmet Keles (New York University), with the seminar “Fisher-Hartwig asymptotics for non-Hermitian random matrices” Abstract: In this talk, I will present the two-dimensional analogue of the asymptotics for Toeplitz determinants with Fisher-Hartwig singularities, for general real symbols. A key focus of the talk will be the surgery method we developed to handle these singularities and establish global asymptotics. I will also discuss applications of this result, including the convergence of the characteristic polynomial of random normal matrices to Gaussian Multiplicative Chaos measure. Based on joint work with Paul Bourgade, Guillaume Dubach, and Lisa Hartung. We encourage in-person partecipation. Should you be unable to come, here is the link to the Teams streaming: Seminar: Keles | Join meeting in Teams | Microsoft Teams <https://teams.microsoft.com/meet/350026120586403?p=39yQDfTb2SlgxQXC1W> The seminar is part of the Excellence Project MatMod@TOV.

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Sylvia Fruehwirth-Schnatter Seminar at Ca' Foscari University of Venice - 20 April 2026
by Roberto CASARIN 13 Apr '26

13 Apr '26

Dear Colleagues Professor Sylvia Fruehwirth-Schnatter (Institute for Statistics and Mathematics, WU Vienna University of Economics and Business, Austria) will give the seminar: Skew Sparse Bayesian Factor Analysis Monday, April 20 at 12:15 CEST, Meeting Room 1, by the Department of Economics, San Giobbe Campus, Ca' Foscari University of Venice It will be possible also to attend on Zoom here: https://unive.zoom.us/j/83783375271?pwd=va9ph6IbOQmMth9FJMCtelXv7ahUeu.1 All the interested people are warmly invited to attend! Abstract: Factor analysis is a popular method to obtain a sparse representation of the covariance matrix of multivariate observations and to uncover the unobserved driving factors behind observed correlation. A challenge for factor models is to estimate the unknown number of factors and to recover an interpretable factor loading matrix from the data. Research in the area of sparse Bayesian factor analysis successfully addresses these issues within a Bayesian framework through the help of variable selection and shrinkage priors, see Frühwirth-Schnatter, Hosszejni and Lopes, 2025 for a recent review. Most approaches to sparse Bayesian factor analysis, however, rely on the assumption that the idiosyncratic errors are Gaussian. In the present talk, this restrictive assumption is alleviated by assuming that the idiosyncratic error follow Azzalini’s multivariate skew-normal or skew-t distribution. Such a non-Gaussian factor model has a stochastic representation as a Gaussian factor model with an additional factor following a truncated standard normal distribution and the skewness parameters acting a factor loadings. This representation is exploited in the present talk to perform sparse Bayesian inference and learn the number of factors and the sparse loading matrix also for non-Gaussian factor models. Applications to financial time series will serve as an illustration. More information available here: https://www.unive.it/data/agenda/3/109034 -- Roberto Casarin, PhD Professor of Econometrics Ca' Foscari University of Venice San Giobbe 873/b - 30121 Venezia, Italy http://sites.google.com/view/robertocasarin/ https://www.unive.it/vera <https://www.unive.it/isba2024>

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[SURE-AI @ STAR Seminars] Wed Apr 22 - Luca Galimberti
by Leonardo Tarquini 13 Apr '26

13 Apr '26

Dear all, Join us for our upcoming talk in the SURE-AI @ STAR seminar<https://www.mn.uio.no/math/english/research/groups/risk-stochastics/star-se…> series on Wednesday, April 22nd, 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/69338752617>. The speaker is Luca Galimberti (King's College London) with the talk: Title: Deep Learning methods for Limit Order Books: an Infinite-Dimensional Perspective Abstract: Moving from the optimal liquidation problems proposed by Abi Jaber and Neuman (2024), we study operator learning in the context of linear propagator models with transient price impact à la Bouchaud et al. (2004) and Gatheral (2010). Transient price impact persists and decays over time according to some square integrable propagator kernel H. More specifically, we show that the optimal execution strategy u = u(H) depends continuously on H, therefore giving rise to a highly non-linear continuous solution operator S between suitable infinite-dimensional Banach spaces. In view of an appropriate infinite-dimensional Universal Approximation Theorem, this operator S can in turn be approximated via ad hoc neural architectures, offering a quick to evaluate surrogate of the operator S in rapidly varying market conditions. The seminar is in the interest of SURE-AI - Sustainable, Risk-Averse and Ethical AI<https://www.sure-ai.no>. We are looking forward to seeing you! Best regards, Giulia, Leonardo, Pere, and David

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Next Webinar PRISMA - April 13, 2026 - Speakers: Jodi Dianetti & Giorgio Ferrari
by Luciano Campi 13 Apr '26

13 Apr '26

Webinar of the team UMI - PRISMA (http://www.umi-prisma.polito.it/) PRISMA webinars follow a colloquium-style format designed to foster exchange and discussion within the Italian probability and statistics community. Each session features two speakers, who give two closely connected 30-minute talks providing the community with a perspective on their research area. Over the past few years, recordings of the seminars have been made available on the UMI YouTube channel: https://youtube.com/playlist?list=PLmySpc-jrtAMq84VH71evyqPc1hl6eEQb The next event is scheduled for Monday, April 13, 2026. The speakers will be Jodi Dianetti (Università di Roma Tor Vergata) and Giorgio Ferrari (University of Bielefeld), who will speak on: Singular Stochastic Controls in Reinforcement Learning and Mean-field Problems According to the following schedule 16:00 1st seminar 16:30 Break and discussions 16:45 2nd seminar 17:15 Conclusions and discussions The abstract can be found below. The seminars will be streamed on Teams at the following link: <https://teams.microsoft.com/meet/336647845045160?p=BZrq2TCGqLcOqxzVsv> teams.microsoft.com<https://teams.microsoft.com/meet/336647845045160?p=BZrq2TCGqLcOqxzVsv> [X]<https://teams.microsoft.com/meet/336647845045160?p=BZrq2TCGqLcOqxzVsv> We look forward to seeing many of you there! Luciano Campi, Maurizia Rossi %%%%%%%%%%%%%%%%%%%%%%%%%%%% SPEAKERS: Jodi Dianetti (Università di Roma Tor Vergata) and Giorgio Ferrari (Bielefeld University) TITLE: Singular Stochastic Controls in Reinforcement Learning and Mean-field Problems ABSTRACT: This talk is divided into two parts, both devoted to stochastic control problems with singular controls. In both cases, a connection with optimal stopping plays a key role, although it arises in different ways and from different perspectives. In the first part, we consider optimal stopping problems from a reinforcement learning perspective. We formulate the stopping decision through randomized stopping times, modeled by bounded, nondecreasing, càdlàg control processes, and introduce an entropy regularization that promotes exploration. The resulting problem can be rewritten as a degenerate, finite-fuel singular stochastic control problem. Using dynamic programming, we characterize the optimal exploratory policy, obtain semi-explicit solutions in a real-option setting, analyze the vanishing-entropy limit, and propose a policy-iteration reinforcement learning algorithm with convergence guarantees. In the second part, we turn to mean-field control problems with singular controls over a finite horizon, allowing for general dependence on the distribution of the state. We show that these problems can be linked to a mean-field game with singular controls, and that equilibria of this game yield optimal controls for the original problem. For a mean-field version of the classical monotone follower problem, the associated equilibrium is characterized by exploiting its connection with optimal stopping together with a Kakutani-Fan-Glicksberg fixed-point argument, leading to a complete characterization of the optimal control in terms of a moving free boundary that uniquely solves a nonlinear integral equation. The talk is based on (ongoing) joint works with Andrea Amato, Federico Cannerozzi, and Renyuan Xu. --------------------------------------------------------

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Liuren Wu Seminar - University of Florence, DISEI, April 21
by Federico Maglione 12 Apr '26

12 Apr '26

Dear Colleagues, We are pleased to announce that Prof. Liuren Wu will be visiting the Department of Economics and Management (DISEI) at the University of Florence and will deliver a seminar on Tuesday, April 21st. Speaker: Liuren Wu (Zicklin School of Business, Baruch College, City University of New York) Title: Separate Risk from Optionality Abstract: Investors are averse to risk but love convex payoffs. This paper proposes to use a security’s delta and vega exposures to differentiate the contributions from linear risks and convex payoffs. We construct the delta and vega exposures on the stock and bond of a company through a classic structural model representation, and build a joint stock and bond return factor model linking their return variation to their delta and vega exposure estimates. The delta factor portfolio targeting linear asset return risk generates a significantly positive average excess return. The vega portfolio targeting the optionality exposure generates a significantly negative average excess return. The separation of asset return risk from optionality sheds light on several market observations, including the distress puzzle in the stock and bond markets, the bet-against-beta anomaly, and time-varying stock-bond co-movements. The seminar will be held in person at 2:45 PM at DISEI, Via delle Pandette 9, 50127 Florence, Aula Bracco (1st floor, Building D6). Best Regard, Federico Maglione, PhD Assistant Professor of Mathematical Finance Erasmus+ Delegate ¦ Degree in Sustainable Business for Societal Challenges UNIVERSITY OF FLORENCE Department of Economics and Management Via delle Pandette, 9, 50127 Firenze

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Openings in Math at Wrocław Tech
by Krzysztof Bogdan 11 Apr '26

11 Apr '26

Dear Colleagues! The Faculty of Pure and Applied Mathematics at Wrocław University of Science and Technology is one of Poland's leading centers for mathematical research. We have a few faculty openings for Assistant Professors and Associate Professor with deadlines 3 or 7 May, respectively: https://euraxess.ec.europa.eu/jobs/424923 https://euraxess.ec.europa.eu/jobs/424891 https://euraxess.ec.europa.eu/jobs/424927 https://euraxess.ec.europa.eu/jobs/425905 We also have 12 positions for PhD students (deadline 2 June): https://szd.pwr.edu.pl/en/for-candidates/admission-procedure Please forward to those interested. With best regards, Krzysztof Bogdan

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JOBS | 2 PhDs and 1 postdoc position in statistics/ML, University of Oslo (Norway)
by Valeria Vitelli 10 Apr '26

10 Apr '26

Dear all, three fully funded positions in (bio)statistics/ML are available at the Oslo Centre for Biostatistics and Epidemiology <https://www.med.uio.no/imb/english/research/centres/ocbe/>, University of Oslo (UiO), Norway. See the details below. I would be very grateful if you could share the vacancies with talented candidates who might be interested in the positions. All the best, Valeria ---------------------------------------------------------------------------------------------------------------- *PhD positions: *We are looking for two motivated PhD candidates to work at the intersection of machine learning, probabilistic modelling, and genetics. - Project 1: The goal is to develop a new class of methods for analysing tensors with complex latent dependencies, using machine learning models combined with efficient Bayesian inference (e.g., variational approximation) - Project 2: The goal is to develop a new class of generative models for discrete sequence data, combining diffusion models and coalescent theory The *3-years postdoc position *is linked to a project recently funded by the Research Council of Norway concerning Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of probabilistic recommender systems. *Salary & quality of life:* Norway offers competitive PhD / postdoc salaries, typically around 2,500-3000€ net per month, with a cost of living comparable to large European cities (Paris, London). Healthcare is free and Oslo is wonderful (ski slopes accessible by metro). All three positions will be connected to Integreat, the Norwegian Centre for Knowledge-driven ML <https://www.integreat.no/>, already gathering around 25 PhD students and a lively and stimulating environment for an early-career researcher; the hired candidates will also be involved in the broader activities of my larger research group on Statistical models for high-dimensional and functional data <https://www.med.uio.no/imb/english/research/groups/statistics-high-dimensio…> . *More info and how to apply* 👉 PhD position 1 (deadline *April 19th*): https://www.jobbnorge.no/en/available-jobs/job/297729/phd-position-in-stati… PhD position 2 (deadline *end of April*): link to apply shall be posted on Monday here <https://www.med.uio.no/imb/english/research/groups/statistics-high-dimensio…> Postdoc position (deadline *April 19th*): https://www.jobbnorge.no/en/available-jobs/job/297730/postdoc-position-in-s… Contact persons / supervisors: William Denault (williade(a)uio.no) Valeria Vitelli ( valeria.vitelli(a)medisin.uio.no) -- Valeria Vitelli Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, University of Oslo, Norway group page: https://www.med.uio.no/imb/english/research/groups/statistics-high-dimensio… <https://www.med.uio.no/imb/english/research/groups/statistics-high-dimensio…> mailto: valeria.vitelli(a)medisin.uio.no

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Call for application PhD in Economics Ca' Foscari University a.y. 2026-27 - spread the news!
by Antonella Basso 10 Apr '26

10 Apr '26

Dear colleague, The call for applications for the PhD in Economics at Ca' Foscari University of Venice is now open and published here: https://www.unive.it/web/it/259/bando-annuale [ITALIAN] https://www.unive.it/web/en/2161/annual-call <https://www.unive.it/web/en/2161/annual-call> [ENGLISH] We offer 5 positions with fully funded scholarships for 4 years starting from September 2026 and a position for a self-funded foreign candidate. The amount of a scholarship is about 20.000 euros gross/year. From the first year, PhD students can count on 1624,30 euros/year for conference participation or summer/winter schools. *Deadline to apply: May 6th 2026 at 1:00 PM (Italian time).* The PhD program aims to prepare a selected group of students for an academic career, as well as for positions in research sectors of international organizations, public institutions, private companies, central banks, and financial institutions. The wide range of research interests and the international reputation of Ca’ Foscari’s faculty in economics, econometrics, finance, and quantitative fields, along with the rich program of internationally renowned seminars and workshops organized by the department, provide students with a stimulating environment throughout their PhD studies. Students receive appropriate support, including financial aid, to participate in international conferences and workshops and to compete in the international job market. Perspective candidates can register to a Zoom information session on Wednesday April 15th 2026 at 4:00pm <https://www.unive.it/data/agenda/3/114192> (CEST) and get to know our world-class program, faculty, placement and more. The link is: https://forms.gle/6rUiuKgXdef8LYDA9 For information on the PhD programme in Economics: http://www.unive.it/phd-economics Best regards Antonella Basso ********************************************************************************************** Cara/o Collega, Ti scrivo per segnalare l'apertura del bando per il programma di dottorato in Economics offerto dal Dipartimento di Economia dell'Università Ca’ Foscari. Quest'anno sono disponibili 5 posti con borsa quadriennale (circa 20.000 € annui per l'intera durata del dottorato), più un posto per studenti stranieri in possesso di borsa di studio propria. * Il bando si chiude il 6 maggio 2026 alle 13.00.* Il dottorato ambisce a preparare un gruppo selezionato di studenti per la carriera accademica, ma anche per ricoprire posizioni nei settori della ricerca di organizzazioni internazionali, istituzioni pubbliche, imprese private, banche centrali e istituzioni finanziarie. L'ampio spettro di interessi di ricerca e la reputazione internazionale del Dipartimento di Economia in area economica, econometrica, finanziaria, e quantitativa, così come il ricco programma di seminari e workshop di livello internazionale organizzati in dipartimento permettono agli studenti di lavorare in un ambiente stimolante per tutta la durata del corso di dottorato. Gli studenti ricevono adeguato supporto, anche economico, per partecipare a conferenze e workshop internazionali e per poter competere sul job market internazionale. Il *15 aprile alle ore 16.00* in Zoom è organizzato un incontro informativo sul dottorato. E' richiesta la registrazione: https://forms.gle/6rUiuKgXdef8LYDA9 <https://forms.gle/6rUiuKgXdef8LYDA9> Il bando è disponibile a questo link: https://www.unive.it/web/it/259/bando-annuale Informazioni dettagliate sul PhD in Economics di Ca’ Foscari: http://www.unive.it/phdeconomics Cordiali saluti Antonella Basso -- Antonella Basso Dipartimento di Economia Università Ca' Foscari Venezia Fondamenta S. Giobbe - Cannaregio 873 30121 Venezia - Italy Tel. +39-041-2346914 E-mail address:basso@unive.it Web page:https://www.unive.it/data/persone/5591751

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ABS (Applied Bayesian Statistics) school on "Interpretable Bayesian Learning,for Physical and Engineering Sciences" in Como, Italy (July 6-10, 2026)
by ELISA VARINI 10 Apr '26

10 Apr '26

Dear all, We are glad to inform you that ABS26, the next Applied Bayesian Statistics school, running since 2004, will be held in the city of Como (Italy), along the Lake Como shoreline at the beautiful Villa del Grumello, on July 6-10, 2026. The school is organised by CNR IMATI (Institute of Applied Mathematics and Information Technologies at the Italian National Research Council in Milano), in cooperation with Fondazione Alessandro Volta. The topic will be Interpretable Bayesian Learning for Physical and Engineering Sciences. The lecturer will be Prof. Simon Mak (Department of Statistical Science, Duke University), a leading expert in integrating domain knowledge (e.g., scientific theories, mechanistic models, guiding principles) as prior information for cost-efficient statistical inference, prediction, and decision-making, with the support of Yen-Chun Liu (Department of Statistical Science, Duke University), a brilliant PhD student of Prof. Mak, specializing in Bayesian optimization, Gaussian processes, and reinforcement learning. If interested, you can register on the school website: https://abs26.imati.cnr.it/ Early registration fees are available until April 30, 2026. As in the past, there will be a combination of theoretical and practical sessions, along with presentations by participants on their work (past, present, and future) related to the school's topic. OUTLINE: This course investigates the rising topic of interpretable statistical learning, motivated by timely needs from modern scientific and engineering applications. For such applications, state-of-the-art machine learning methods often yield analyses that are uninterpretable to scientists, which greatly obfuscates scientific findings and decision-making. Interpretable Bayesian learning provides an elegant and effective solution by embedding scientific principles (e.g., boundary conditions, mechanistic equations) within its prior specification. In this course, we will cover a broad spectrum of interpretable Bayesian learning methods (with theory and algorithms), providing a cohesive roadmap for this recent and rapidly-evolving area of study. This will be complemented by practical case studies from ongoing projects in particle physics, mechanical engineering, and bioengineering. Emphasis will be made on novel directions for research in this promising area. Topics will cover - Fundamentals of Gaussian process (GP) surrogate modeling: prediction, parameter inference, experimental design - Decision-making with GP surrogates: Bayesian optimization, active learning, Bayesian inverse problems - Markov Chain Monte Carlo (MCMC) methods - Boundary-informed GP modeling - Shape-constrained (e.g., monotone, isotonic, convex) GP modeling - Mechanistic GP modeling - Physics-integrated neural networks, its Bayesian variants and recent developments - Dynamical system recovery: SINDy, Bayesian SINDy, and recent developments We hope you will be interested in the school and we would like to meet you in Como. We invite you also to share the information with people potentially interested. Best regards Elisa Varini and Fabrizio Ruggeri Executive Director and Director of ABS26

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