Kyriaki Kalimeri

Machine Learning for Social Good: Algorithmic & Data Challenges when working with Vulnerable Populations

by Dr. Kyriaki Kalimeri
Researcher at ISI Foundation, Turin, Italy
Senior Research Consultant at UNICEF HQ, New York, USA

When and Where

7th July 2025, 15:00-16:30

Building Γ2, University Campus

Abstract

The scale, reach, and real-time nature of the Internet is opening new frontiers for better serving humanity, and particularly for a deeper understanding of the vulnerabilities in our societies, including inequalities and fragility in the face of a changing world. Vulnerable populations including children, elderly, racial or ethnic minorities, socioeconomically disadvantaged, underinsured, or those with certain medical conditions, are often absent in commonly used data sources. The aim of this talk will be to shed light on data and algorithmic biases, as well as methodological particulars when addressing vulnerable populations, drawing insights from case studies in response to real humanitarian crises.

Language: English

About the Speaker

Kyriaki Kalimeri is a researcher at the ISI Foundation, Turin, Italy, and a Senior Research Consultant at UNICEF, New York,  while previously she was a research assistant at the Fondazione Bruno Kessler, Trento, Italy. She received her Ph.D. degree from the University of Trento in 2013, while was a visiting Ph.D. at the Human Dynamics Group at MIT Media Lab, Cambridge, USA. She holds a Diploma in Electrical and Computer Engineering from the Technical University of Crete in 2008. Her current research interests lie at the intersection of computational social science and engineering, and in particular on employing statistical machine learning and natural language processing for humanitarian response.