Seminars 

 

“D2 Seminar Series” is a series of seminars organized by the Florence Center for Data Science that invites members and fellows of the Center (and not only) to present their current researches or academic work. It takes place twice a month, Fridays from 2-3.30 pm. People are invited to attend and the registration (free of charge) is available one week before the event on the website (under the Events page).

 

“Special Guest Seminar Series” is a particular seminar series organized by the Florence Center for Data Science that invites researchers and distinguished academicians from external university institutions to hold a lecture about their current research or academic work. It takes place several times during the year. People are invited to attend and the registration (free of charge) is available one week before the event on the website (under the Events page).

3rd Edition D2 Seminar Series

Björn Bornkamp - "Special Guest Seminar Series"

11TH OF May 2023

Björn Bornkamp – Statistical Methodologist at Novartis presented a seminar on

“ Estimand and analysis strategies for recurrent event endpoints in the presence of a terminal event

Abstract:

Recurrent event endpoints are commonly used in clinical drug development. One example is the number of recurrent heart failure hospitalizations, which is used in the context of clinical trials in the chronic heart failure (CHF) indication. A challenge in this context is that patients with CHF are at an increased risk of dying. For patients who died, further heart failure hospitalizations can no longer be observed. As a treatment may affect both mortality and the number of hospitalizations, a naive comparison of the number of hospitalizations across treatment arms can be misleading even in a randomized clinical trial. An investigational treatment may, for example, reduce mortality compared to a control, but this may lead to more observed hospitalizations if severely ill patients with high risk of repeated hospitalizations die earlier under the control treatment. In this talk we will review this issue and different estimand and analysis strategies. We will then describe a Bayesian modelling strategy to target a principal stratum estimand in detail. The model relies on joint modelling of the recurrent event and death processes with a frailty term accounting for within-subject correlation. The analysis is illustrated in the context of a recent randomized clinical trial in the CHF indication.

The recording of the seminar is available here.

Guido Imbens Nobel Lecture

Economics Lecture by Nobel Prize 2021: Guido W. Imbens

28th of March 2023, from 11:30 AM -13.00 pm:

The Florence Center for Data Science and the Department of Statistics, Computer Science, Application “G. Parenti” – DiSIA in a joint event with the Department of Economics of the European University Institute – EUI organized the Economics Lecture by Nobel Nobel Prize in Economics 2021 Guido W. Imbens

Guido Imbens – The Applied Econometrics Professor and Professor of Economics, Graduate School of Business, Stanford University – The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, 2021 hold a lecture on

“Combining Experimental and Observational Data”

Abstract:
In the social sciences there has been an increase in interest in randomized experiments to estimate causal effects, partly
because their internal validity tends to be high, but they are often small and contain information on only a few variables. At the same time, as part of the big data revolution, large, detailed, and representative, administrative data sets have become more widely available. However, the credibility of estimates of causal effects based on such data sets alone can be low.
In this paper, we develop statistical methods for systematically combining experimental and observational data to improve the credibility of estimates of the causal effects. We focus on a setting with a binary treatment where we are interested in the effect on a primary outcome that we only observe in the observational sample. Both the observational and experimental samples contain data about a treatment, observable individual characteristics, and a secondary (often short term) outcome. To estimate the effect of a treatment on the primary outcome, while accounting for the potential confounding in the observational sample, we propose a method that makes use of estimates of the relationship between the treatment and the secondary outcome from the experimental sample. We interpret differences in the estimated causal effects on the secondary outcome between the two samples as evidence of unobserved confounders in the observational sample, and develop control function methods for using those differences to adjust the estimates of the treatment effects on the primary outcome. We illustrate these ideas by combining data on class size and third grade test scores from the Project STAR experiment with observational data on class size and both third and eighth grade test scores from the New York school system.

Co-author: Susan Athey and Raj Chetty

The registration of the lecture is available here.

DiSIA Christmas Lecture F. Mealli

DiSIA Xmas Lecture 2022

22th of December 2022, from 11:00 AM -13.30 pm:

The Department of Statistics, Computer Science, Applications “G. Parenti” together with the Florence Center for Data Science organized the 2023 Christmas Lecture:

Fabrizia Mealli –Professor of Statistics at the Department of Statistics, Informatics, Applications “G. Parenti” – DiSIA of the University of Florence hold a lecture on

“Causal inference: past, present, future

Click here to download the slides of the lecture.

Kosuke Imai - "Special Guest Seminar Series"

7TH OF October 2022, FROM 10.30-11.30 PM:

Kosuke Imai – Harvard University will present a seminar on

“Statistical Inference for Heterogeneous Treatment Effects and Individualized Treatment Rules Discovered by Generic Machine Learning in Randomized Experiments

Abstract: Researchers are increasingly turning to machine learning (ML) algorithms to estimate heterogeneous treatment effects (HET) and develop individualized treatment rules (ITR) using randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain HET or produce efficacious ITR under practical settings with many covariates and small sample size. In addition, the quantification of estimation uncertainty remains a challenge. We develop a general approach to statistical inference for estimating HET and evaluating ITR discovered by a generic ML algorithm. We utilize Neyman’s repeated sampling framework, which is solely based on the randomization of treatment assignment and random sampling of units.  Unlike some of the existing methods, the proposed methodology does not require modeling assumptions, asymptotic approximation, or resampling methods. We extend our analytical framework to a common setting, in which the same experimental data is used to both train ML algorithms and evaluate HET/ITR. In this case, our statistical inference incorporates the additional uncertainty due to random splits of data used for cross-fitting.

Here you can download the slides of the Seminar.

Data Science Xmas Lecture 2021

16th of December 2021, from 3-4.30 pm:

Marina Vannucci Noah Harding Professor of Statistics, Rice University holds a lecture on

Bayesian Models for Microbiome Data with Variable Selection

AbstractI will describe Bayesian models developed for understanding how the microbiome varies within a population of interest. I will focus on integrative analyses, where the goal is to combine microbiome data with other available information (e.g. dietary patterns) to identify significant associations between taxa and a set of predictors. For this, I will describe a general class of hierarchical Dirichlet-Multinomial (DM) regression models which use spike-and-slab priors for the selection of the significant associations. I will also describe a joint model that efficiently embeds DM regression models and compositional regression frameworks, in order to investigate how the microbiome may affect the relation between dietary factors and phenotypic responses, such as body mass index. I will discuss the advantages and limitations of the proposed methods with respect to current standard approaches used in the microbiome community and will present results on the analysis of real datasets. If time allows, I will also briefly present extensions of the model to mediation analysis.

Click here for all the information to participate

“Young Researchers Seminar Series” is a particular seminar series organized by the Florence Center for Data Science that invites young researchers and Ph.D. students to hold a lecture about their current research or academic work. It takes place several times during the year. People are invited to attend and the registration (free of charge) is available one week before the event on the website (under the Events page).

Seminar Alberto Cassese & Chiara Bocci

17th OF March 2023, FROM 2.30-4 PM:

Alberto Cassese from the Department of Statistics, Computer Science, Applications “G. Parenti” of the University of Florence presented a seminar on

“Bayesian negative binomial mixture regression models for the analysis of sequence count and methylation data”

Chiara Bocci from the Department of Statistics, Computer Science, Applications “G. Parenti” of the University of Florence presented a seminar on 

“Sampling design for large-scale geospatial phenomena using remote sensing data”

Click here to access the abstracts of the seminar

Seminar Augusto Cerqua & Marco Letta

3rd OF March 2023, FROM 2.30-4 PM:

Augusto Cerqua and Marco Letta from the Department of Statistical Sciences, Sapienza University of Rome presented a seminar on

“”Losing control (group)? The Machine Learning Control Method for counterfactual forecasting”.”

Click here to access the abstracts of the seminar

Matt DosSantos DiSorbo

22th May 2023

Matt DosSantos DiSorbo from Harvard Business School presented a seminar on

“Starting Strong: The Impact of Early Interventions on Employee Outcomes

Abstract:

In randomized experiments with insufficient covariates, confounders can bias point estimates. We introduce rank estimates in factorial designs and discuss their relative robustness. We argue that, in many applied settings, identifying the top-ranked intervention is more critical than recovering exact point estimates. Using data from an experiment conducted at a large financial firm, our method provides evidence that interventions in the first week of an internship have the largest sustained effect on intern rating. Further, the data is suggestive that these early interventions have the greatest impact on interns eventually accepting an extended offer. This principle — intervene early — has important managerial implications.

The recording of the seminar is available here.

Riccardo Michielan

28th OF February 2023, FROM 2.30-4 PM:

Riccardo Michielan from University of Twente presented a seminar on

“Is there geometry in real networks?”
Abstract: In the past decade, many geometric network models have been developed, assuming that each vertex is associated a position in some underlying topologic space. Geometric models formalize the idea that similar vertices are naturally likely to connect. Moreover, these models are able reproduce many properties which are commonly observed in real networks. On the other hand, it is not always possible to infer the presence of geometry in real networks, if the edge connections are the only observables. The aim of this talk is to formalize a simple statistic which counts weighted triangles: this statistic discounts the triangles that are almost surely not caused by geometry. Then, using weighted triangles we will be able to elaborate a robust technique to distinguish whether real networks are embedded in a geometric space or not.

Click here to access the abstracts of the seminar

Seminar Elena Stanghellini & Gianluca Iannucci

17th OF February 2023, FROM 2.30-4 PM:

Elena Stanghellini from Department of Economics, University of Perugia presented a seminar on

“Causal effects for binary variables: parametric formulation and sensitivity”

Gianluca Iannucci from the Department of Economics and Management, University of Florence presented a seminar on

“The interaction between emission tax and insurance in an evolutionary oligopoly”

Click here to access the abstracts of the seminar

Seminar Nicola Del Sarto & Andrea Mercatanti

3rd OF February 2023, FROM 2.30-4 PM:

Nicola Del Sarto from the Department of Economics and Management of the University of Florence presented a seminar on

“One size does not fit all. Business models heterogeneity among Internet of Things architecture layers”

Andrea Mercatanti from the Department of Statistical Sciences, Sapienza University of Rome presented a seminar on

“A Regression Discontinuity Design for ordinal running variables: evaluating Central Bank purchases of corporate bonds.” (Joint work with F. Li, T. Makinen, A. Silvestrini)

Click here to access the abstracts of the seminar

Seminar Giacomo Toscano & Gabriele Fiorentini

20TH OF January 2023, FROM 2.30-4 PM:

Giacomo Toscano from the Department of Economics and Management of the University of Florence presented a seminar on

“Central limit theorems for the Fourier-transform estimator of the volatility of volatility”

Gabriele Fiorentini from the Department of Statistics, Computer Science, Applications “G. Parenti” of the University of Florence presented a seminar on

“Specification tests for non-Gaussian structural vector autoregressions

Click here to access the abstracts of the seminar

Iavor Bojinov

29TH OF JUNE 2022, FROM 4-5 PM:

Iavor Bojinov – Harvard Business School presented a seminar on

Design & Analysis of Dynamic Panel Experiments

Abstract: Over the past few years, firms have begun to transition away from the static single intervention A/B testing into dynamic experiments, where customers’ treatments can change over time within the same experiment. This talk will present the design-based foundations for analyzing such dynamic (or sequential experiments), starting with the extreme case of running an experiment on a single unit—what’s known as time-series experiments. Next, motivated by my work to understand if humans or algorithms are better at executing large financial trades, I will lay out a framework for designing and analyzing switchback experiments, a special case of time-series experiments. Then, I will explain how to extend this framework to multiple units and what happens when these units are subject to population interference (the setting where one unit’s treatment can impact another’s outcomes). Finally, if time allows, I will conclude with a brief discussion of an empirical study that leveraged over 1,000 experiments conducted at LinkedIn to quantify the additional benefits of adopting dynamic experimentation.

Seminar Monica Bianchini & Giulio Bottazzi

25TH OF NOVEMBER 2022, FROM 2.30-4 PM:

Monica Bianchini from the Department of Information Engineering and Mathematics of the University of Siena presented a seminar on

A gentle introduction to Graph Neural Networks

Giulio Bottazzi from the Institute of Economics of the Sant’Anna School of Advanced Studies of Pisa presented a seminar on

Persistence in firm growth: inference from conditional quantile transition matrices

Click here to access the abstracts of the seminar

Dante Amengual

17th of June 2022, from 2-3 pm:

Dante Amengual – CEMFI presented a seminar on

“Hypothesis tests with a repeatedly singular information matrix

Abstract: We study score-type tests in likelihood contexts in which the nullity of the information matrix under the null is larger than one, thereby generalizing earlier results in the literature. Examples include multivariate skew-normal distributions, Hermite expansions of Gaussian copulas, purely non-linear predictive regressions, multiplicative seasonal time series models, and multivariate regression models with selectivity. Our proposal, which involves higher-order derivatives, is asymptotically equivalent to the likelihood ratio but only requires estimation under the null. We conduct extensive Monte Carlo exercises that study the finite sample size and power properties of our proposal and compare it to alternative approaches.

Seminar Gianmarco Bet & Agnese Panzera

11TH OF November 2022, FROM 2.30-4 PM:

Gianmarco Bet from the Department of Mathematics and Computer Science “Ulisse Dini” of the University of Florence presented a seminar on

Detecting anomalies in geometric networks

Agnese Panzera from the Department of Statistics, Computer Science, Applications “G. Parenti” of the University of Florence presented a seminar on

Density estimation for circular data observed with errors

Click here to access the abstracts of the seminar

Seminar Alessio Brini & Matteo Pedone

28TH OF OCTOBER 2022, FROM 2.30-4 PM:

Alessio Brini from Duke University Pratt School of Engineering presented a seminar on

“Reinforcement Learning Policy Recommendation for Interbank Network Stability
(joint work with Gabriele Tedeschi and Daniele Tantari)”

Matteo Pedone from the Department of Statistics, Computer Science, Applications “G. Parenti” of the University of Florence presented a seminar on

A Bayesian nonparametric approach to personalized treatment selection

Click here to access the abstracts of the seminar

Seminar Claudio Durastanti & Cecilia Viscardi

14th OF October 2022, FROM 2-3.30 PM:

Claudio Durastanti from the Department of Basic and Applied Sciences for Engineering (SBAI) of Sapienza University presented a seminar on

Spherical Poisson Waves

Cecilia Viscardi from the Department of Statistics, Computer Science, Applications “G. Parenti” of the University of Florence presented a seminar on

Likelihood-free Transport Monte Carlo

Click here to access the abstracts of the seminar

2nd Edition D2 Seminar Series

 

Seminar Georgia Papadogeorgou & Joseph Antonelli

13th OF may 2022, FROM 10-11.30 PM:

Georgia Papadogeorgou from the Department of Statistics of the University of Florida presented a seminar on 

“Unmeasured spatial confounding

Joseph Antonelli from the Department of Statistics of the University of Florida presented a seminar on

“Heterogeneous causal effects of neighborhood policing in New York City with staggered adoption of the policy

Click here to access the abstracts of the seminar

Seminar Andrea Barucci & Alessandra Mattei

22nd of April 2022, from 2-3.30 pm:

Andrea Barucci from IFAC-CNR Institute of Applied Physics presented a seminar on

Exploring Egyptian Hieroglyphs with Convolutional Neural Networks

Alessandra Mattei from the Department of Statistics, Computer Science, Applications “G. Parenti”, University of Florence presented a seminar on

Selecting Subpopulations for Causal Inference in Regression Discontinuity Designs (Joint work with Laura Forastiere e Fabrizia Mealli)

Click here to access the abstracts of the seminar

Seminar Fabio Schoen & Alessandro Panunzi & Lorenzo Gregori

8TH OF April 2022, FROM 3-4.30 PM:

Fabio Schoen from the Department of Information Engineering, University of Florence presented a seminar on

Clustering for Optimization, Optimization for Clustering

Alessandro Panunzi & Lorenzo Gregori from the Department of Humanities, University of Florence presented a seminar on

Towards action concepts identification through unsupervised and semi-supervised clustering on a multimodal cross-linguistic ontology

Click here to access the abstracts of the seminar

Seminar Brunero Liseo & Ernesto De Vito

25TH OF March 2022, FROM 2.30-4 PM:

Brunero Liseo from the Department of Methods and Models for Economics, Territory, and Finance of Sapienza University presented a seminar on

ABCC: Approximate Bayesian Conditional Copulae (with Clara Grazian and Luciana Dalla Valle)”

Ernesto De Vito from the Department of Mathematics of the University of Genova presented a seminar on

Understanding Neural Networks with Reproducing Kernel Banach Spaces

Click here to access the abstracts of the seminar

Seminar Daniela Bubboloni

11TH OF FEBRUARY 2022, FROM 2.00-3.00 PM:

Daniela Bubboloni from the Department of Mathematics and Computer Science “Ulisse Dini” presented a seminar on

Paths and flows for centrality measures in networks

You can download the full paper here

Click here to access the abstracts of the seminar

Click here to access the Q&A

Seminar Marco Pangallo & Fiammetta Menchetti

25th OF February 2022, FROM 2.30-4 PM:

Marco Pangallo from the Sant’Anna School of Advanced Studies presented a seminar on

Making a housing market agent-based model learnable

Fiammetta Menchetti from the Department of Statistics, Computer Science, Applications “G. Parenti” presented a seminar on

Combining counterfactual outcomes and ARIMA models for policy evaluation

Click here to access the abstracts of the seminar

Seminar Fabio Corradi & Michela Baccini

11th OF February 2022, FROM 2.30-4 PM:

Fabio Corradi from the Department of Statistics, Computer Science, Applications “G. Parenti” of the University of Florence presented a seminar on

Learning the two parameters of the Poisson-Dirichlet distribution with a forensic application

Michela Baccini from the Department of Statistics, Computer Science, Applications “G. Parenti” presented a seminar on

Combining and comparing regional epidemic dynamics in Italy: Bayesian meta-analysis of compartmental models and model assessment via Global Sensitivity Analysis

Click here to access the abstracts of the seminar

Seminar Lorenzo Seidenari & Francesco Calabrò 

28th of January 2022, from 2.30-4 pm:

Lorenzo Seidenari from the Department of Information Engineering of the University of Florence presented a seminar on

Predicting Multiple Future Trajectories for Safe Self-Driving Cars

Francesco Calabrò from the Department of Mathematics and Applications “Renato Caccioppoli” of the University of Naples “Federico II” presented a seminar on

The use of neural networks for the resolution of Partial Differential Equations

Click here to access the abstracts of the seminar

Seminar Andrea Marino & Raffaele Guetto

10th of December 2021, from 2-3.30 pm:

Andrea Marino from the Department of Statistics, Computer Science, Applications “G. Parenti” presented a seminar on

Italy’s lowest-low fertility in times of uncertainty

Raffaele Guetto from the Department of Statistics, Computer Science, Applications “G. Parenti” presented a seminar on

Approximating the Neighborhood Function of (Temporal) Graphs

Click here to access the abstracts of the seminar

Seminar Giorgio Ricchiuti & Marco Bertini

26th of November 2021, from 2-3.30 pm:

Giorgio Ricchiuti from the Department of Economics and Management presented a seminar on

State Space Model to Detect Cycles in Heterogeneous Agents Models

Marco Bertini from the Department of Information Engineering presented a seminar on

High quality video experience using deep neural networks”

Click here to access the abstracts of the seminar

Seminar Luigi Brugnano & Veronica Ballerini

12th of November 2021, from 2-3.30 pm:

Luigi Brugnano from the Department of Mathematics and Computer Science “Ulisse Dini” presented a seminar on

Recent advances in bibliometric indexes and their implementation

Veronica Ballerini from the Department of Statistics, Computer Science, Applications “G. Parenti” presented a seminar on

Fisher’s Noncentral Hypergeometric Distribution for the Size Estimation of Unemployed Graduates in Italy

Click here to access the abstracts of the seminar

Seminar Giulia Iorio & Massimo Fornasier

29th of October 2021, from 2-3.30 pm:

Giulia Iorio from the Department of Economics, School of Social Science of the City University of London presented a seminar on

Performance-based research funding: Evidence from the largest natural experiment worldwide

Massimo Fornasier from the Department of Mathematics of the Technical University of Munich presented a seminar on

Consensus-based optimization

Click here to access the abstract of the seminar

Seminar Leonardo Bargigli & Chiara Marzi

15th of October 2021, from 2-3.30 pm:

Leonardo Bargigli from the Department of Economics and Management, University of Florence presented a seminar on

Endogenous and Exogenous Volatility in the Foreign Exchange Market (with G. Cifarelli)”

Chiara Marzi from the Institute of Applied Physics ‘Nello Carrara’ (IFAC) – National Research Council (CNR) presented a seminar on

Artificial Intelligence in Neuroimaging”

Click here to access the abstracts of the seminar

Click here to access the recording of the seminar

 

1st Edition D2 Seminar Series

 

Seminar Anna Gottard & Costanza Conti

2nd of July – FROM 2-3.30 PM

Anna Gottard from the Department of  Statistics, Computer Science, Applications “G. Parenti” presented  a seminar on

Circular data, conditional independence & graphical models”

Costanza Conti from the Department of Industrial Engineering presented a seminar on

Penalized hyperbolic-polynomial splines” (Joint work with: Rosanna Campagna, Universit`a degli Studi della Campania “L. Vanvitelli”)

Click here to access the abstracts of the seminar

Seminar Enrico Ravera & Gherardo Chirici

18th of June 2021, from 2-3.30 pm

Enrico Ravera from the Magnetic Resonance Center (CERM) and Department of Chemistry presented a seminar on

“From algebra to biology: what does the math of ensemble averaging methods can tell us”

Gherardo Chirici from the research unit COPERNICUS Earth Observation and Spatial Analysis and the Department of Agriculture, Food, Environment, and Forestry presented a seminar on

“Big data from space. Recent Advances in Remote Sensing Technologies” 

Click here to access the abstracts of the seminar

Seminar Cesare Bracco & Leonardo Boncinelli

4th of June 2021, from 2-3.30 pm

Cesare Bracco from the Department of Mathematics and Computer Science “Ulisse Dini”, University of Florence presented a seminar on

Scattered data: surface reconstruction and fault detection” (joint work with O. Davydov, C. Giannelli, D. Großmann, S. Imperatore, D. Mokriš, A. Sestini)

Leonardo Boncinelli from the Department of Economics and Management, University of Florence presented a seminar on

Game-based education promotes sustainable water use”

Click here to access the abstracts of the seminar

Seminar Fabrizia Mealli & Andrew Bagdanov

21st of May 2021, from 2-3.30 pm:

Fabrizia Mealli from the Department of Statistics, Computer Science, Applications “G. Parenti” presented a seminar on

Assessing causality under interference”

Andrew Bagdanov from the Department of Information Engineering, University of Florence presented a seminar on

Lifelong Learning at the end of the (new) Early Years”

Click here to access the abstracts of the seminar