Skip to main content

David Hyland

Personal photo - David Hyland

David Hyland

Doctoral Student



I am interested in incentives as a framework for understanding and promoting coordination in multi-agent systems. My work integrates concepts from rational verification, game theory, and active inference to advance our understanding of hierarchical agency and how collective intelligence arises.

My research explores methods and theories of incentive design to shape the collective behaviour of multi-agent systems. This includes both top-down incentive design and endogenous transfer mechanisms. Additionally, I have worked on partition function games and non-Markovian reinforcement learning.

I welcome opportunities for collaboration and discussion in these research areas.


I am a third-year DPhil student supervised by Michael Wooldridge and Julian Gutierrez. Prior to Oxford, I studied at the University of Sydney and undertook several research projects as an undergraduate. I completed a summer research scholarship and research assistantship with Gauthier Voron and Vincent Gramoli working on performance benchmarking for the DBFT consensus algorithm on the Corda blockchain. Following this, I initiated a TSP project with Peter Kim, where I studied, implemented, and built animated visualisations of 2D agent-based models of immune cell interactions in C++. In the summer before my final year as an undergraduate, I did a research internship in bioinformatics at The Kinghorn Cancer Centre where I devised and implemented an automated hyperparameter optimisation method based on binary search and wrote a parallelised implementation of a Nanopore DNA analysis algorithm using SIMD. During my honours year, I studied and implemented an entropy-regularised continuous time Reinforcement Learning algorithm under the supervision of Zhou Zhou.