School of Computer Science and Statistics
This project requires the student to construct an application to support citizen science and engagement in the monitoring and data collection of coastal regions, particularly salt marshes. The application will introduce the user to the range of plants and animals and encourage them to investigate and survey areas of marsh to support ongoing sustainability research … Read more
Humans are sometimes slow to recognise change over time – the shifting baseline syndrome – and this presents a challenge in the understanding of how much our planet and it’s various spheres have already changed. A personalized understanding of the rate of change of the planetary boundaries during an individual’s own lifetime may increase their … Read more
** This project is only available for students in the MSc in Statistics & Sustainability programme only** “The ‘Climate Change in the Irish Mind’ study (CCIM) is a nationally representative study of the Irish people’s beliefs, attitudes, policy preferences and behaviours regarding climate change. The Wave 1 baseline survey of CCIM was undertaken in 2021 … Read more
**This project is for students in the MSc Statistics and Sustainability only. No other student will be accepted for this project.** This project seeks to review what datasets are available in an Irish context around sustainability and climate change (e.g., EPA Climate Change in the Irish Mind Survey, SEAI Survey of Irish Attitudes to Wind … Read more
I have supervised many projects involving the design and prototype development of apps and am happy to do more. Past examples include a mobile app to support development of patient self-efficacy, a mobile app to support suicide watch teams on the Corrib in Galway, a web application for supporting virtual work team productivity, and a … Read more
Increasingly, patients gather data relevant to their healthcare on their phones and via wearable or home-based sensors. When this data is intended for healthcare professionals it is known as patient generated health data (PGHD). But getting that data into a form that can be shared seamlessly with the healthcare system is a challenge. And clinicians … Read more
The raw output of a language neural net model is a set of probabilities over the possible next word (or token). That is then converted into text output by a decoding step. Standard decoding — greedy, beam search, or independent sampling — commits to each token or reasoning step without any lookahead about whether it’s … Read more
Classical mutation testing applies a small, fixed catalog of mutations to code, e.g. flipping + to – or changing True to False. But this produces mutated code that often doesn’t resemble the kinds of mistakes real developers actually make. In this project you will build a mutation-testing pipeline around a direct comparison: does learning to … Read more
Fine-tuning language models on sensitive text (medical notes, private messages, internal documents) risks the model memorizing and later regurgitating specifics from the training data — a well-documented failure mode for even small models. Differential privacy (DP), via DP-SGD, gives a formal, quantifiable guarantee against this by clipping per-example gradients and adding calibrated noise during training. … Read more
Plain Monte-Carlo Tree Search (MCTS) relies on random rollouts (simulations of future game moves) to estimate the value of a game position. AlphaZero’s key insight was to replace random rollouts with a learned neural network that biases the tree search toward promising moves, cutting the number of simulations needed for strong play. In this project … Read more