Pansanella Valentina

Valentina Pansanella is a Research Fellow at the National Research Council of Italy (ISTI-CNR), specializing in computational network science and diffusion dynamics. Her work bridges theoretical models with practical applications in social and epidemiological contexts.

Her research focuses on complex network analysis, particularly examining algorithmic bias, information diffusion, and homophily measurement in dynamic networks. Key contributions include developing computational frameworks like NDlib and CDLIB for modeling diffusion processes and community detection. Her work frequently employs agent-based simulations and Python-based tooling to analyze contagion patterns in social and biological systems.

Analysis of her publication trends reveals consistent focus on network topology effects (2017-2022), evolving from foundational diffusion models to specialized applications in fake news perception (2020) and epidemic modeling (2020). Recent work demonstrates increasing sophistication in path-aware homophily metrics (2021) and topology-aware bias modeling (2022).

As part of the KDD Lab research ecosystem, she collaborates extensively with Gianni Rossetti and Letizia Milli on network science tool development. Her technical contributions center on creating open-source libraries that enable reproducible network analysis across academic and applied domains.