School of Computer Science and Statistics
This project investigates algorithmic bias and fairness in machine learning systems. The student will analyse whether a predictive model produces unequal outcomes for different demographic or protected groups and evaluate techniques for measuring and mitigating unfairness. A focus will be on using and extending the OxonFair python toolkit. This project would be ideal for BA … Read more
Project descriptor: This project explores how machine learning models can estimate uncertainty in their predictions and use a reject option, allowing the model to abstain from making predictions when confidence is too low. The aim is to improve the reliability and safety of automated decision-making systems. This project would be ideal for BA ICS/MCS, BA … Read more
This project investigates interpretable machine learning methods that explain model predictions using examples. The focus will be on prototypes, which represent typical examples of a class or decision, and counterfactuals, which show how an input would need to change to receive a different prediction. Students will explore and compare state-of-the-art (SOTA) approaches. Interpretability in prediction … Read more
LetsEncrypt is currently the most important X.509 CA issueing (free) certificates for web servers. Web servers interact with LetsEncrypt via the ACME protocol (RFC8555). Since the basic ACME RFC was published (in 2019) a number of extensions and profiles have been defined by the IETF’s ACME working group. The project here is to survey those … Read more
The project is to check what (various) browsers and/or other DNS stubs/recursives and public recursives (e.g. quad-1,8,9) support and use in terms of TLS 0-RTT when DoT/DoH /DoQ are used. Having established the state of current deployments, the next goal is to check whether or not a 0-RTT replay attack works or fails in common … Read more
Creating Virtual Reality experiences normally requires specialist software and significant programming experience. This project will investigate how web-based 3D and generative AI tools can make VR creation accessible to children, allowing them to create a 3D world in a browser and then immediately experience it inside a VR headset. The student will develop a child-friendly … Read more
People perform the same actions in subtly different ways, creating an individual motion signature. This project will investigate whether these characteristics are preserved—or lost—when human motion is learned by a generative animation model. Using Epic Games’ new AnimGen framework and the HiPHI motion-capture dataset, the student will select a small number of performers performing similar … Read more
Recent generative animation models can create realistic character motion rather than simply replaying existing animation clips. In this project, you will use Epic Games’ new AnimGen framework and motion-capture data from the large-scale HiPHI dataset to investigate human-object interaction. The student will select a manageable subset of interactions, such as approaching, reaching for, picking up … Read more
In Virtual Reality, users typically expect their avatar to both look and move like them. But what happens when your virtual body responds to your actions while moving with the motion style of somebody else, or when your appearance is replaced by a highly realistic digital double of another person? In this project, the student … Read more
How we move through a crowd is influenced not only by where other people are, but also by how we perceive them. This project will investigate whether the appearance and proximity of virtual people influence how users behave when navigating through a crowd in Virtual Reality. The student will develop a VR crowd environment in … Read more