School of Computer Science and Statistics
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
Mobility is the lifeblood of human connectedness and economic progress, and roads are a critical component of the transportation system for both people and goods. Unfortunately, roads are potentially vulnerable to medium- to long-term disruptions (ie, lasting hours to days) due to extreme weather, infrastructure failures, accidents, maintenance, and unexpected demand all resulting in high … Read more
Virtual crowds typically rely on a limited set of motion-capture clips, which can lead to visible repetition and reduce the perceived diversity and realism of the crowd. This project will investigate whether Epic Games’ new AnimGen generative animation framework can be used to create more varied and individualised motion for virtual crowds. The student will … Read more
This project investigates methods for explaining anomalies detected in time series data. The aim is not only to identify when an anomaly occurs, but also to provide understandable explanations of why the observation or time period was considered anomalous. The project may explore feature importance, subsequence explanations, prototype examples, counterfactuals, or other explainable AI techniques … Read more
This project evaluates guardrail or safety models designed to detect, prevent, or filter unsafe and undesirable outputs from large language models (LLMs). The focus is on developing a systematic evaluation framework and comparing the effectiveness of different guardrail approaches. This project would be ideal for BA ICS/MCS, BA CS (JH), BA CSLL and integrated masters. … Read more
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