Alex McAvoy

Alex McAvoy is an Assistant Professor in the School of Data Science and Society at the University of North Carolina at Chapel Hill. He holds a postdoctoral background in the Center for Mathematical Biology at the University of Pennsylvania. His research focuses on evolutionary dynamics, game theory, multi-agent learning, and network science, particularly examining how behaviors spread in populations and the emergence of prosocial behaviors in structured networks. McAvoy's work bridges applied mathematics with biological systems, exploring pathologies like inequality amplification from prosocial actions and the role of selfishness in population dynamics.

His academic trajectory includes affiliations with Harvard University, University of British Columbia, and Shanghai Jiao Tong University through collaborations. He has published extensively since 2015, with key contributions on asymmetric evolutionary games, dynamic networks, and fixation probabilities in evolutionary processes. McAvoy’s publications often emphasize interdisciplinary applications of mathematical models to biological and social systems.

Recent research highlights include studies on imitation dynamics in incomplete information networks (2023), strategy evolution on dynamic networks (2023), and evolutionary instability of selfish learning in repeated games (2022). His work consistently addresses theoretical frameworks with empirical relevance, such as multilayer population structures and public goods dilemmas in heterogeneous societies (2020).

McAvoy collaborates with leading researchers in mathematical biology and network science, including Martin Nowak (Harvard), Christoph Hauert (UBC), and Qi Su (Shanghai Jiao Tong). His research has been cited over 1,500 times, reflecting significant impact in evolutionary game theory and complex systems analysis.