Network Science of AI

We explore the intersection of "Networks & AI", investigating how connectivity patterns within both natural and artificial learning systems influence learning outcomes, performance, and overall robustness. Central to this work is the exploration of the underlying mechanisms of human cognition, the evolution of AI models, and the study of the collaboration between humans and AI agents within complex environments. Our research also addresses issues of trustworthy Machine Learning in network science, to mitigate the risks of using ML and ensure transparency, fairness, and reliability in artificial intelligence systems.

Our focus