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David Hyland

Personal photo - David Hyland

David Hyland

Doctoral Student



My research interest lies in a multidisciplinary approach to studying hierarchical goal-directed behaviour in multi-agent systems. I draw inspiration from a variety of fields including computer science, mathematics, neuroscience, and psychology.

My current research is on computational models for incentive design and rational verification in multi-agent systems. The objective is to study methods for top-down influence on the collective behaviour of multi-agent systems.


I am a second-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.