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PhD position in Applied Mathematics and Statistics, Göteborg, Sweden
by Umberto Picchini 19 Feb '22

19 Feb '22

We are looking for a doctoral student who would like to work in *any of the research areas* of the division of Applied Mathematics and Statistics <https://www.chalmers.se/en/departments/math/organisation/Pages/applied-math…> at Chalmers University of Technology an University of Göteborg, Göteborg, Sweden. A list of possible projects is given below. PhD salaries in Sweden are attractive. The following list includes a collection of possible projects that you can work in: Marina Axelson-Fisk: AI Support for Medical Decision Making <https://www.chalmers.se/sv/institutioner/math/organisation/Documents/PhD%20…> Tobias Gebäck, Alexei Heintz and Irina Pettersson: Multiscale models for wetting dynamics in porous materials <https://www.chalmers.se/sv/institutioner/math/organisation/Documents/PhD%20…> Philip Gerle: Universal differential equations for infectious disease modelling <https://www.chalmers.se/sv/institutioner/math/organisation/Documents/PhD%20…> Erik Kristiansson: Analysis of DNA sequences using artificial intelligence <https://www.chalmers.se/sv/institutioner/math/organisation/Documents/PhD%20…> Anders Logg: High-Performance High-Quality Automated Mesh Generation for Large-Scale City Modeling and Simulation <https://www.chalmers.se/sv/institutioner/math/organisation/Documents/PhD%20…> Serik Sagitov: Critical Galton-Watson processes with overlapping generations <https://www.chalmers.se/sv/institutioner/math/organisation/Documents/PhD%20…> Aila Särkkä: Spatio-temporal modelling combined with machine learning <https://www.chalmers.se/sv/institutioner/math/organisation/Documents/PhD%20… Spatio-temporal modelling combined with machine learning.pdf> Feel free to contact any of the people above or other people in the division that you might be interested in working with already before submitting your application. For full info, contact details and links to apply, please go to https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pag… <https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pag…> *Application deadline: February 25, 2022* * * -- _________________________________________________________ Umberto Picchini, Associate Professor, PhD, Docent https://umbertopicchini.github.io/ , twitter: @uPicchini

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seminar: "Combined analysis of spatially misaligned data using Gaussian fields and the stochastic partial differential equation approach.", Paula Moraga 22 February
by Umberto Picchini 19 Feb '22

19 Feb '22

You are welcome to the next Statistics seminar at Dept of Mathematical Sciences at Chalmers and Göteborg University. We are very glad to have, on Tuesday February 22, Paula Moraga <https://www.paulamoraga.com/> (KAUST) who will talk of: ///"Combined analysis of spatially misaligned data using Gaussian fields and the stochastic partial differential equation approach."/ //** paula moraga *About the speaker: *Paula Moraga <https://www.paulamoraga.com/> is an Assistant Professor of Statistics at King Abdullah University of Science and Technology (KAUST) and the Principal Investigator of the GeoHealth research group. Her research focuses on the development of innovative statistical methods and computational tools for geospatial data analysis and health surveillance, and the impact of her work has directly informed strategic policy in reducing disease burden in several countries. She has developed modeling architectures to understand the geographic and temporal patterns and identify targets for intervention of diseases such as malaria in Africa and cancer in Australia, and has worked on the development of a number of R packages for Bayesian risk modeling, detection of disease clusters, and risk assessment of travel-related spread of disease. // //* * *Abstract: *Spatially misaligned data are becoming increasingly common due to advances in both data collection and management in a wide range of scientific disciplines including the epidemiological, ecological and environmental fields. Here, we present a Bayesian geostatistical model for fusion of data obtained at point and areal resolutions. The model assumes that underlying all observations there is a spatially continuous variable that can be modeled using a Gaussian random field process. The model is fitted using the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE) approaches. In the SPDE approach, a continuously indexed Gaussian random field is represented as a discretely indexed Gaussian Markov random field (GMRF) by means of a finite basis function defined on a triangulation of the region of study. In order to allow the combination of point and areal data, a new projection matrix for mapping the GMRF from the observation locations to the triangulation nodes is proposed which takes into account the types of data to be combined. The performance of the model is examined via simulation when it is fitted to point, areal, and point and areal data combined to predict several simulated surfaces that can appear in real settings. The model is also applied to predict the concentration of fine particulate matter (PM2.5) in Los Angeles and Ventura counties, USA, during 2011. The results show that the combination of point and areal data provides better predictions than if the method is applied to just one type of data, and this is consistent over both simulated and real data. We conclude the approach presented may be a helpful advance in the area of spatial statistics by providing a useful tool that is applicable in a wide range of situations where information at different spatial resolutions needs to be combined. *Feel free to spread this announcement in your network.* * * *Where*: https://chalmers.zoom.us/j/64709763394 Password: 920248 ** **** *When*: Tuesday 22 February at 14.15-15.15*(Swedish time)*. ** -- _________________________________________________________ Umberto Picchini, Associate Professor, PhD, Docent https://umbertopicchini.github.io/ , twitter: @uPicchini

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Seminar José Figueroa Lopez in Verona, 23/2/22 at 12, Efficient Volatility Estimation for Lévy Processes with Jumps of Unbounded Variation
by Cecilia Mancini 16 Feb '22

16 Feb '22

José Figueroa Lopez Professor at the Washington University in St. Louis will give, both on site and on line, the SEMINAR Efficient Volatility Estimation for Lévy Processes with Jumps of Unbounded Variation Abstract. Statistical inference for stochastic processes based on high-frequency observations has been an active research area for more than a decade. One of the most well-known and widely studied problems is that of estimation of the quadratic variation of the continuous component of an Itô semimartingale with jumps. Several rate- and variance-efficient estimators have been proposed in the literature when the jump component is of bounded variation. However, to date, very few methods can deal with jumps of unbounded variation. By developing new high-order expansions of the truncated moments of a Lévy process, we construct a new rate- and variance-efficient estimator for a class of Lévy processes of unbounded variation, whose small jumps behave like those of a stable Lévy process with Blumenthal-Getoor index less than 8/5. The proposed method is based on a two-step debiasing procedure for the truncated realized quadratic variation of the process. Our Monte Carlo experiments indicate that the method outperforms other efficient alternatives in the literature in the setting covered by our theoretical framework. All interested people are warmly invited to participate Professor Figueroa-Lopez is visiting our department from February the 10th to March the 22nd, and from June the 15th to August the 15th For attendance via Zoom, please register at the following page, we will send you the meeting link: https://docs.google.com/forms/d/e/1FAIpQLSdJ6PccwEy8tSEngi0JMUKYEJ4yOHuuwur… Live attendance: the Department of Economics, via Cantarane 24, Vaona room. Due to the limited number of available seats, interested people should write an e-mail to: cecilia.mancini(a)univr.it<mailto:cecilia.mancini@univr.it>

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Scientific ASA 2022 conference on Data-Driven Decision Making
by Marta Nai Ruscone 15 Feb '22

15 Feb '22

Apologies for cross-posting.... Dear Colleagues, we would like to draw your attention to the upcoming Scientific ASA 2022 Conference on "Data-Driven Decision Making" that will be held at the University of Genoa (Italy), 12-14 September 2022. Attached is the Call for Paper. For further information and updates please visit the conference website asa2022.unige.it We are looking forward to Welcome you in Genova! Best Regards, Enrico di Bella and Corrado Lagazio (co-chairs of the Local Organising Commitee) *** --- *** <> Marta Nai Ruscone Department of Economics - DIEC University of Genova. Via Vivaldi, 5. 16100 Genova (GE). Italy

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International conference “Statistical Methods and Models for Complex - SAVE THE DATE!
by Alessandra Fabbri Colabich 11 Feb '22

11 Feb '22

*Si invia il seguente messaggio da parte della Direzione del Dipartimento di Scienze Statistiche dell'Università degli Studi di Padova:* *SAVE THE DATE!International conference “Statistical Methods and Models for Complex* Data”, *21-23 September 2022*, Padova, Italy The Department of Statistical Sciences of the University of Padova is organizing the international conference: “Statistical Methods and Models for Complex Data”. The conference will be held in Padova, Italy on 21-23 September 2022. The event is organized on the occasion of the 800th anniversary of the University of Padua and the last year of the excellence project of our department. The scientific program will include plenary sessions, with 45 minutes invited presentations from internationally recognized experts, followed by 25 minutes for interventions of two main discussants and informal moments of discussion and interaction between the participants. Partecipation of senior and young scientists involved in the developments of statistical methods and tools for complex data is strongly encouraged. The scientific program of the conference will be available as soon as possible on the website http://800years.stat.unipd.it, currently under development. For further information, please contact: 800years(a)stat.unipd.it

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Seminar in Statistics - GRAHAM CORMODE
by Pierpaolo De Blasi 11 Feb '22

11 Feb '22

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Venerdi 18 Febbraio 2022, alle ore 12.00, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Speaker: *Graham Cormode* (University of Warwick) Title: *New Lower and Upper Bounds for Quantile Summary Algorithms* Abstract: Finding the median, or more generally quantiles, is a core problem in data analysis. The question has been heavily studied in streaming and related models of computation, for over four decades. In this talk I will present some recent advances: - Lower bounds for approximating quantiles in the deterministic comparison model, for additive error, which show that the best known algorithm is in fact optimal - Upper bounds for relative error epsilon-approximations of quantiles, which improves over previous results and exceed the best known lower bounds by only an O(log(1/e)3/2) factor. This covers joint work with Pavel Vesely, Justin Thaler, Edo Liberty and Zohar Karnin. ------------------------------------------------ Sarà possibile seguire il seminario anche in streaming: Join Zoom Meeting <https://us02web.zoom.us/j/88206863118?pwd=cmlHYzBXbW9NZ2JVYmtDbDNqNnFydz09> Meeting ID: 882 0686 3118 Passcode: 757710 Il seminario è organizzato dalla "de Castro" Statistics Initiative www.carloalberto.org/stats Cordiali saluti, Pierpaolo De Blasi -- Pierpaolo De Blasi University of Torino & Collegio Carlo Alberto carloalberto.org/pdeblasi <https://sites.google.com/a/carloalberto.org/pdeblasi/>

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Third Italian Meeting on Probability and Mathematical Statistics
by Tiziano Vargiolu 10 Feb '22

10 Feb '22

Dear Colleagues, we are pleased to recall some essential information about the Third Italian Meeting on Probability and Mathematical Statistics (Bologna, Italy, June 13th-16th, 2022) Important deadlines: - March 30, 2022: submission of Organized Session proposals (https://site.unibo.it/probstat/en/how-to-contribute) - March 30, 2022: submission of abstracts of all contributions (https://site.unibo.it/probstat/en/how-to-contribute) - April 7, 2022: notification of acceptance will be sent to the authors - April 21, 2022: early registration (with reduced fee) - May 19, 2022 intermediate registration Main links: Conference web site: https://site.unibo.it/probstat/en Guidelines for authors: https://site.unibo.it/probstat/en/how-to-contribute Plenary Speakers: https://site.unibo.it/probstat/en/about-1/plenary Registration: https://site.unibo.it/probstat/en/registration Accommodation: https://site.unibo.it/probstat/en/for-participants/accommodation Travel info: https://site.unibo.it/probstat/en/for-participants/travel Contacts: https://site.unibo.it/probstat/en/contacts We look forward meeting you soon. The Scientific Committee Claudia Ceci, Paolo Dai Pra, Antonio Di Crescenzo, Franco Fagnola, Marco Ferrante, Franco Flandoli, Antonio Lijoi, Domenico Marinucci, Andrea Pascucci, Franco Pellerey, Laura Sacerdote The Local Organizing Committee Fabio Antonelli, Elena Bandini, Massimo Campanino, Andrea Cosso, Marco Di Francesco, Alberto Lanconelli, Stefano Pagliarani, Andrea Pascucci, Pietro Rigo, Tiziano Vargiolu

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(PMS)^2 online talk: Michele Coghi, Monday February 14 at 17.30
by Carlo Orrieri 09 Feb '22

09 Feb '22

Dear colleagues, We are happy to announce the following online talk: Speaker: Michele Coghi (Università d Trento) Title: Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering. Abstract: Motivated by the challenge of incorporating data into misspecified and multiscale dynamical models, we study a McKean-Vlasov equation that contains the data stream as a common driving rough path. This setting allows us to prove well-posedness as well as continuity with respect to the driver in an appropriate rough-path topology. The latter property is key in our subsequent development of a robust data assimilation methodology: We establish propagation of chaos for the associated interacting particle system, which in turn is suggestive of a numerical scheme that can be viewed as an extension of the ensemble Kalman filter to a rough-path framework. Finally, we discuss a data-driven method based on subsampling to construct suitable rough path lifts and demonstrate the robustness of our scheme in a number of numerical experiments related to parameter estimation problems in multiscale contexts. Based on arXiv:2107.06621 <https://arxiv.org/abs/2107.06621>. Date and time: Monday February 14, 17:30-18:30 (Rome time zone) Zoom link: https://us02web.zoom.us/j/88138955113?pwd=R1Vpa2xWVDlFc2pjUXIxSWpWU21LQT09 <https://us02web.zoom.us/j/88138955113?pwd=R1Vpa2xWVDlFc2pjUXIxSWpWU21LQT09> ID riunione: 881 3895 5113 Passcode: 672537 This talk is the second of the (PMS)^2: Pavia-Milano Seminar series on Probability and Mathematical Statistics organized jointly by the universities Milano-Bicocca, Pavia, Milano-Politecnico and Milano-Statale. Participation is free and welcome! (though limited to 100 participants for technical reasons) Best regards The organizers (Mario Maurelli, Carlo Orrieri, Maurizia Rossi, Margherita Zanella)

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Online workshop announcement
by Alessandra Micheletti 08 Feb '22

08 Feb '22

*Big Data challenges for Mathematics: state of the art and future perspectives* *Online webinar – February 25, 2022* The workshop will be held on the platform Zoom and will be streamed on YouTube. Participants who would like to follow the workshop in real time and participate to the discussion with the speakers are requested to register. See the web site of the workshop for registration, programme and additional information: *http://itn-bigmath.unimi.it/* <http://itn-bigmath.unimi.it/> *Aims of the workshop:* Nowadays the data deluge is the hallmark of a new kind of ‘Law of Large Numbers’ that builds intelligence from large, heterogeneous, noisy and, in general, complex data sets collected from mobile devices, the Internet of Things, software logs, automated medical devices, social media, and so many other data sources. The classical mathematical and statistical paradigms are often not applicable to current real-world problems, so there is a growing demand of new mathematical and statistical techniques to face such problems, able to shed some light on the often black-box techniques which are usually applied in such context and which characterise Deep Learning and, more generally, Artificial Intelligence. On the other side, since computers can not do everything by themselves, there is a growing need for new professional and scientific figures, the data scientists, that master a whole range of skills, ranging from data processing to sophisticated math tools and computational skills that are needed to extract the knowledge. The state of the art and future research perspectives in this framework will be highlighted and discussed in this webinar by the PhD students enrolled in the EU funded MSCA Project BIGMATH <http://itn-bigmath.unimi.it/> (grant n. 812912), starting from a set of challenging industrial case studies. Additionally some well known keynote speakers will introduce their point of view on possible future perspectives in different specific and quite hot subject areas related with the analysis of complex and big data. -- ------------------------------------ Alessandra Micheletti Associate Professor - Probability and Mathematical Statistics Dept. of Environmental Science and Policy - ESP Università degli Studi di Milano via Saldini 50, 20133 Milano, Italy phone: +39-02503-16130 fax: +39-02503-16090 https://alessandramichelettiwebpage.wordpress.com/

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Seminar by Sara Svaluto-Ferro in Padova.
by Giorgia Callegaro 07 Feb '22

07 Feb '22

Dear all, it's a pleasure to announce the next Probability and Finance seminar at the Department of Mathematics of the University of Padova, which will be held both *in presence* and online with the following details: - Date: 25 February 2022 - Speaker: Dr. Sara Svaluto-Ferro (Univ. of Verona) - Venue: Dept of Mathematics, Univ. of Padova, room 2BC30 - Zoom link: available at https://www.math.unipd.it/~bianchi/seminari/ - Title: "*Signature processes in mathematical finance, an introduction*" - Abstract: we will provide an introduction to the signature of a continuous semimartingale. This in particular includes its definition, its main properties, and an overview of (some) of its uses in financial mathematics. Thanks and hope to see you soon, Giorgia -- 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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