[ETIS – Lab Seminar] On the Many Facets of Fairness and Explainability in Graph Data

Date: 30/03/2026
Time: 13h30
Place: ENSEA (room to be defined)

Speaker: Prof. Evaggelia Pitoura, University of Ioannina

Title: On the Many Facets of Fairness and Explainability in Graph Data

Abstract:
As AI systems are increasingly used in domains with societal impact, ensuring fairness and transparency has become a central challenge. In this talk, I will present an overview of our recent research on fairness, explainability, and their interplay, focusing on graph data, graph-based learning tasks and knowledge graphs. I will discuss multiple facets of fairness in data graphs, ranging from lack of bias in knowledge graph tasks to structural properties such as connectivity, and examine the challenges of explaining decisions and outcomes in graph settings, including counterfactual explanations. More broadly, the talk will highlight fairness and explainability as closely connected dimensions of responsible graph data management.

Bio:
Evaggelia Pitoura is a Professor at the Department of Computer Science and Engineering at the University of Ioannina and a Lead Researcher at Archimedes Research Unit, Athena RC, Greece. She holds a BEng degree from the University of Patras, Greece, and an MS and PhD from Purdue University, USA. Her current research interests focus on two primary areas: responsible data management, with a focus on fairness, explainability, and their interplay; and on graph exploration and analysis. For her work, he has received best paper awards, a Marie Currie Fellowship and two Recognition of Service Awards from ACM. She is an ACM senior member, founding chair of the Hellenic ACM SIGMOD chapter, and member of the sectorial scientific council of Greece National Council for Research, Technology and Innovation.