IWSM is one of the major activities of the Statistical Modelling Society, founded with the purpose of promoting and encouraging statistical modelling in its widest sense. The workshop aims to involve both academic and professional statisticians and data analysts with a particular focus on real data problems which involve an element of novel statistical modelling, or novel model application.
The atmosphere of the workshop is friendly and supportive, with no parallel sessions, with the aim of stimulating the exchange of ideas and experiences related to statistical modelling.
Papers focusing on applications with important substantive implications as well as methodological issues are welcome, including new developments in Data Science. Submissions by students and young researchers are particularly encouraged.
The SMS and IWSM strongly encourage students to submit posters and papers: best posters, papers and presentations from students will compete for some great awards!
IWSM 2022 is also sponsored by the Italian Statistical Society (SIS).
New information about the 36th IWSM will be continuously added on this website.
For further information please visit also the websites of the Statistical Modelling Society journal and of the history of the IWSM conference.
Note: this Conference is going to be in presence, so in case of the persistence of Covid-19 Pandemic the Conference will not be held online.
Please, note that according to the Italian Governament laws, from April 30th the Green Pass for Covid-19 will be not required.
If you have any questions or comments, please contact us at info@iwsm2022.com.
EXTENDED DEADLINE FOR ABSTRACT SUBMISSION: 18 APRIL
EXTENDED NOTIFICATION OF REVIEW/ACCEPTANCE: 17 MAY
University of Warwick
Professor of Statistics in the Department of Statistics at the University of Warwick and Turing Fellow of The Alan Turing Institute, which is the UK’s national institute for data science and artificial intelligence.
Ioannis' core research interests are in the theory and methodology of statistical learning and inference, and, in particular, in penalized and pseudo-likelihood theory and methods, statistical computing and algorithms for regression problems and methods for clustering.
He also engages in interdisciplinary applied work of the kind that involves a real synthesis of approaches and has the potential to generate new advances in statistical learning and inference with broader impact. The applied work he is/s been involved in is in: sports science (modelling high-frequency in-game events in team sports, and uncovering the links between human behaviour, health, fitness and overall well-being); finance (modelling the dynamics of financial indicators with structural dependencies); earthquake engineering (assessment of the vulnerability of the built environment from post-hazard survey data); neuroimaging (regression methods for brain lesions from MRI data and the summarization and visualization of effects); and genetics (inferring changes in genomic network structures).
Last but not least, Ioannis is particularly interested in the design and development of scientific (and not only) software to deliver the advances from his theoretical/methodological efforts and some tools that he finds useful to the Data Science community and more broadly.
Technical University of Munich
The research activities of Prof. Czado (born 1959) concentrate on the field of statistics and data science. Her focus is on the modeling of complex dependencies including regression effects and time / space structures with the help of Vine copula-based models. See Vine Copula Models for further details and developments. These allow the construction of high-dimensional multivariate distributions for data that contain different asymmetrical dependencies for each pair of variables. Computer-aided procedures for selection, estimation and adaptation to complex data structures are developed / optimized. Applications can be found in finance and insurance as well as in engineering, geosciences and life sciences. There are a number of collaborations with various international scientists and industry representatives. In 2019 Prof. Czado published a textbook on analyzing dependent data with Vine copulas.
Swiss Federal Institute of Technology
Anthony Davison has published on a wide range of topics in statistical theory and methods, and on environmental, biological and financial applications. His main research interests are statistics of extremes, likelihood asymptotics, bootstrap and other resampling methods, and statistical modelling, with a particular focus on the first currently.
University of Padova
Associate Professor at the University of Padova since 03/2020.
Interested in Bayesian Nonparametrics, Functional data analysis, multiscale methods, data science, machine learning, extreme value analysis, applied statistics.
Discover the Conference Program, the Short Course Program and the Speakers.
Read more about the location where the Conference will be held and what to do in Trieste.
Read more about the admissions fee and register to the Conference and the Short Course.
Discover how to send your paper and submit it here to have it approved.
The conference will be hosted in the building of the Department of Economics, Busines, Mathematics and Statistics “Bruno de Finetti” of the University of Trieste located in the University Campus. A brand new room with 280 seats is available.
Piazzale Europa, 1, 34127 Trieste TS
The event is going to take place from Sunday 17.07 to Friday 22.07 2022, the short course is scheduled on Sunday, 17.07.
Trieste lies in the north-east part of Italy and has its own airport (https://www.triesteairport.it), that is 40 minutes by car/train from the city center. Besides connection with main italian cities (such as Rome or Naples) there are also direct flights from/to: London, Frankfurt, Valencia. Alternatively, one may fly to the international airport in Venice (connection with all main cities) and then reach Trieste by train (approximately 2 hours). By car, Trieste is far 4 hours from Milan, 3 hours from Bologna, 1.30 hour from Venice and 6 hours from Munich, approximately.
