Personal webpage: https://distefanoalessandro.github.io/

Dr. Alessandro Di Stefano is a Senior Lecturer in Computer Science at Teesside University, School of Engineering, Computing & Digital technologies (SCEDT), Department of Computing & Games.

He received his BSc (2009) and MSc degrees (2012) in Telecommunications Engineering from the Department of Electrical, Electronic and Computer Engineering (DIEEI) at the University of Catania, Italy. He holds a PhD in Systems Engineering from the DIEEI at the University of Catania, Italy, awarded in 2015 with a thesis titled "Evolutionary Dynamics of Social Behaviours on Multilayer Networks".

After his PhD, he worked as postdoctoral researcher at DIEEI, University of Catania, for almost four years, and then as a research associate and teaching assistant at the Department of Engineering, King’s College London (KCL), London, UK, supervised by Prof. Nishanth Sastry. Recently, he worked as a research associate at Computer Laboratory, Department of Computer Science and Technology, University of Cambridge, UK, supervised by Prof. Pietro Liò, with whom he has been collaborating since 2012.

His main interests lie at the intersection of multi-agent systems, game theory, complex networks, and artificial intelligence (AI), including machine learning, deep learning, and emerging LLM-based agent systems. By integrating game-theoretic modelling with multiplex network representations, his work explores emergent behaviours in complex environments and supports the design of innovative and beneficial strategies for society.

Recently, his research has focused on developing methodologies that bridge game theory, network science, and AI governance frameworks, with particular emphasis on ensuring fairness, safety, and robust interactions in multi-agent AI systems.

He has published many peer-reviewed papers in high impact journals and leading international conferences and collaborates with universities and industry partners worldwide. Moreover, he serves on the Council of the Complex Systems Society (CSS) and is also a member of the IEEE (Professional Communication Society; Technical Committee on Computational Life Sciences) and regularly reviewer for leading international journals and conferences such as IEEE Transactions on Mobile Computing, Nature Scientific Reports, IJCAI, ECAI, AAMAS, and CCS, where he has often been invited to join the Technical Program Committee of these events.

• Multi-Agent Systems, Game Theory & Strategic Interaction
• Complex Systems 
• Artificial Intelligence & Machine Learning
• LLM-based Agents & NLP-driven Systems
• Human Cooperation & Social Dynamics
• AI Governance, Safety, & Fairness
• Epidemic Spreading & Diffusion processes

Recently, his work has been focusing on methodologies bridging game theory, network science, and LLM-based agent systems, with applications in AI governance, design automation, and multi-agent decision-making. He is particularly interested in understanding the emergent properties of large-scale AI systems and designing mechanisms to ensure safe and fair interactions.