Archive / INF Seminars / INF_2024_03_14_DeNicola_Giacomo
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Data science in society: Modeling network and public health data

 
 
 

Host: Prof. Ernst-Jan Camiel Wit

 

Thursday

14.03

USI Campus Est, room D1.14, Sector D
10:30 - 11:15
  
 

Giacomo De Nicola
Ludwig-Maximilians-Universität, Germany
Abstract:
Modern society is characterized by an abundance of data, coming in many different shapes and forms. This data wealth naturally comes with additional layers of complexity, thus requiring increasingly sophisticated methodology to extract information from it. Most importantly, each dataset is unique in its own way, and thus requires tailored techniques to reveal its secrets. In this context, statistical models can serve as flexible tools to obtain interpretable insight from different types of data, while at the same time adequately quantifying and accounting for the underlying uncertainty. This seminar will introduce statistical modeling approaches for two common but complex data types, namely network data and public health data. The seminar will then go on to show how the presented methods can be employed to obtain valuable insight on relevant societal issues. More specifically, latent space network models will be used to uncover and map polarization on social media, while an indirect standardization approach will be employed to quantify excess mortality associated with the COVID-19 pandemic across different countries.

Biography:
Giacomo De Nicola is a doctoral candidate in the final stages of his PhD in Statistics at LMU Munich, under the supervision of Prof. Göran Kauermann. Prior to that, he earned an MSc in Economic and Social Sciences at Bocconi University, and a BSc in Statistics at the University of Florence. Giacomo’s research focuses on designing and leveraging modern statistical tools to answer questions posed within the social, political, economic, and healthcare sciences. The overarching goal of his work is to establish and consolidate methodologies that improve our understanding of society, with particular focus on applications with tangible real-world impact. More specifically, his main research interests can be broadly categorized in three areas, namely social network modeling, models for monitoring epidemics, and methods for quantifying the impact of crises. In addition to his methodological work, Giacomo also enjoys collaborating with empirical researchers from diverse fields to provide them with appropriate statistical tools to address their problems, bridging the gap between theory and applications.

Host: Prof. Ernst-Jan Camiel Wit