Biography
Colin Cleveland is a postgraduate researcher in the Department of Informatics at King’s College London, supervised by Dr Bart de Keijzer and Dr Maria Polukarov. His research lies in algorithmic game theory, with a particular focus on computational social choice and voting theory. He studies the computational and strategic foundations of collective decision-making, exploring how algorithmic and behavioural factors shape equilibrium outcomes in elections.
Before joining King’s, Colin collaborated with Dr Hsuan-Wei “Wayne” Lee and Dr Attila Szolnoki on research in evolutionary game theory, developing simulation frameworks to model cooperation in structured populations. In 2020, he worked as a Data Analyst at Fukuoka Financial Group, Japan, contributing to financial data analysis and model visualisation.
At King’s, Colin teaches as a Graduate Teaching Assistant for courses including Elementary Logic, Fundamentals of Computation, and Software Engineering. His broader research interests span computational complexity, behavioural decision-making, and algorithmic design for fair and efficient social systems.
Thesis title and abstract
Complexity and Behaviour in Strategic Models of Elections
Research Interests
- Algorithmic Game Theory
- Computational Social Choice
- Voting Theory and Political Mechanisms
- Evolutionary Game Dynamics
- Computational Complexity in Strategic Decision-Making
Colin’s research explores the algorithmic and strategic principles underlying collective decision-making. He studies how computational complexity constrains rational behaviour in elections and multi-agent systems, drawing on tools from game theory, theoretical computer science, and economics. His work seeks to formalise the mechanisms that govern strategic voting, equilibrium existence, and computational tractability in social choice settings. He also develops simulation-based models to examine cooperative behaviour and evolutionary dynamics, connecting algorithmic theory with behavioural insights and real-world collective systems.
PhD Supervisory Team
Websites
Research
Distributed Artificial Intelligence
Understanding AI in social and economic contexts where an intelligent entity may be interacting with other entities
Research
Distributed Artificial Intelligence
Understanding AI in social and economic contexts where an intelligent entity may be interacting with other entities