{"id":5445,"date":"2023-04-27T15:49:52","date_gmt":"2023-04-27T13:49:52","guid":{"rendered":"https:\/\/datascience.unifi.it\/?post_type=tribe_events&#038;p=5445"},"modified":"2023-05-18T17:14:50","modified_gmt":"2023-05-18T15:14:50","slug":"disia-double-welcome-seminar-fiammetta-menchetti-marta-pittavino","status":"publish","type":"tribe_events","link":"https:\/\/datascience.unifi.it\/index.php\/event\/disia-double-welcome-seminar-fiammetta-menchetti-marta-pittavino\/","title":{"rendered":"DiSIA Double Welcome Seminar &#8211; Fiammetta Menchetti &#038; Marta Pittavino"},"content":{"rendered":"<p><span style=\"text-decoration: underline;\">Speaker:<\/span> Fiammetta Menchetti<\/p>\n<p><span style=\"text-decoration: underline;\">Title:<\/span>\u00a0<em>From high school creativity to cultural heritage conservation:\u00a0a journey in causal inference<\/em><\/p>\n<p><span style=\"text-decoration: underline;\">Abstract:<\/span><\/p>\n<div>\u00a0In this talk, I will provide an overview of my research activity in causal inference for time series data. Starting with<\/div>\n<div>C-ARIMA and Bayesian multivariate structural time series models that were part of my PhD thesis, I\u2019ll then give<\/div>\n<div>you a glimpse into my recent collaborations, including a randomized control trial to assess the impact of FABLAB\u2019s<\/div>\n<div>courses on the creativity of Italian high-school students and a machine learning method for counterfactual forecasting<\/div>\n<div>for short panels in the absence of controls. The talk will then focus on the PNRR research activity, which aims<\/div>\n<div>to study the evolution of the web cracks on Brunelleschi\u2019s Santa Maria del Fiore Dome as part of an ongoing and<\/div>\n<div>fascinating project on cultural heritage conservation<\/div>\n<div><\/div>\n<div>\n<hr \/>\n<\/div>\n<div><\/div>\n<p><span style=\"text-decoration: underline;\">Speaker:<\/span> Marta Pittavino<\/p>\n<p><span style=\"text-decoration: underline;\">Title:<\/span> <em>A tale on statistical methods, and their applications, developed around Europe<\/em><\/p>\n<p><span style=\"text-decoration: underline;\">Abstract<\/span>:<\/p>\n<div>\n<div>\u00a0In this talk, I will present some statistical methods that I exploited for my research. I will begin by presenting<\/div>\n<div>the Additive Bayesian Network (ABN) multivariate methodology, a data-driven technique particularly suitable for<\/div>\n<div>inter-dependent data. I will show two applications of ABN in the veterinary epidemiology field. Then, I will<\/div>\n<div>move to the illustration of a Bayesian hierarchical model applied to nutritional epidemiology. Specifically, this<\/div>\n<div>model relates a measurement error model with a disease model via an exposure model. Afterwards, I will provide<\/div>\n<div>examples of quantile regression and forecasting techniques applied to a specific philanthropic-social dataset on<\/div>\n<div>charitable deductions for tax incentives for the Canton of Geneva population. Last, but not least, I will conclude<\/div>\n<div>this statistical modelling journey by introducing the current demographic project for the \u201cForecasting kinship<\/div>\n<div>networks and kinless individuals\u201d and show the first preliminary results of kinless of countries around Europe.<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Speaker: Fiammetta Menchetti Title:\u00a0From high school creativity to cultural heritage conservation:\u00a0a journey in causal inference Abstract: \u00a0In this talk, I will provide an overview of my research activity in causal &#8230;<\/p>\n","protected":false},"author":12,"featured_media":5065,"template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[35],"class_list":["post-5445","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-seminar","cat_seminar"],"_links":{"self":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/5445","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/users\/12"}],"version-history":[{"count":4,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/5445\/revisions"}],"predecessor-version":[{"id":5543,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/5445\/revisions\/5543"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/media\/5065"}],"wp:attachment":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/media?parent=5445"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tags?post=5445"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events_cat?post=5445"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}