School of Computer Science and Statistics
Reinforcement learning (RL) and especially deep reinforcement learning have emerged as powerful paradigms for learning quasi-optimal sequential decision making strategies (in applications as diverse as game playing and urban traffic control). RL uses an approach based on’ trial and error’ in which agents learn by interacting with their environment. Most RL algorithms assume that the … Read more
Poor travel-time reliability, meaning that travel times for the same journey are highly variable and unpredictable, gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Moreover, being able to offer a high degree of travel-time reliability will facilitate the uptake of sustainable road transportation including future public, shared, … Read more
Poor travel-time reliability, meaning that travel times for the same journey are highly variable and unpredictable, gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Moreover, being able to offer a high degree of travel-time reliability will facilitate the uptake of sustainable road transportation including future public, shared, … Read more
An ideal bus route would offer highly predictable journey times to travellers so that the same journey taken at the same time of day on different occasions would take the same amount of time. While there are many sources of variability in journey times such as traffic conditions, passenger boarding and offloading time, and the … Read more
This project will investigate the use of reinforcement learning to develop a highway journey booking system incorporating a dynamic pricing strategy to allow traffic demand to be shaped in ways that will improve traffic efficiency and enhance sustainability by reducing emissions and fuel consumption. The goal will be to evaluate the potential benefit of the … Read more
Music is central in our society. However, the neural mechanisms leading to the enjoyment of music remain unclear. This project is part of a bigger investigation with multimodal data. One dimension of that data involves eye and pupil dynamics, which are known to reflect neural activity relevant to sound perception. Here, you will analyse eye/pupil … Read more
I am happy to supervise a project in all the areas of computer networking that I am interested in — wireless networking, Machine Learning, Artificial Intelligence and in their application to a wide range of real world settings (healthcare, IoT, structural health monitoring). I am particularly interested in exploring some aspects of quantum computing; for … Read more
Please use this form to arrange a time to meet me to discuss project supervision: Form to arrange a meeting with Y Graham I have the below projects available, all related to Natural Language Processing: Data Collection for Analysis of Language in Video; Video Sentiment Analysis; Automatic Video Transcription; Automatic Identification of bias in Video Language; … Read more
Speech production is a fundamental aspect of human communication, yet its underlying neural intricacies remain largely unexplored. This project aims to investigate how concepts are translated into spoken language by probing the neural mechanisms governing speech production. In this project, you will analyse brain data from electrophysiology to describe various facets of speech production. Through … Read more
Restoring speech communication in individuals that can’t speak or have difficulty speaking (e.g., individuals with ALS) is an important challenge that could benefit many. While many solutions have been proposed that have various limitations, recent progress in machine learning methods (e.g., transformers) open new opportunities. This project aims to decode the intended speech of individuals … Read more