School of Computer Science and Statistics
The project will deal with the statistical analysis of meteorological data. See for example here: 🌤️ Free Open-Source Weather API | Open-Meteo.com The interested Students, must do a good search in this or another relevant data, contact me for confirmation and then they can request the project.
ELIGIBILITY: This project is for a student on the M.Sc. in Statistics and Data Science. In this project, we’ll look at the various ways in which ecologists have attempted to answer the question ‘How many species are there?’. Some of these methods are statistical, and we’ll focus on those, but we’ll also take a look … Read more
My teaching and research relate to natural language processing and machine learning. There’s code I have developed for algorithms relating to this, some traditional and some more novel. There is scope for projects relating to this pre-existing code and algorithms that is not necessarily related to improving the bottom-line performance of these algorithms, but more … Read more
The online OED (see bottom for url ) contains a great deal of information about a word, including ‘etymological’ information on the words ‘origin‘. This info is given near the top of an entry in very terse format, making it accessible really only to specialists. There are several things that could be done to generate … Read more
There is no excerpt because this is a protected post.
There is no excerpt because this is a protected post.
Many learners rely on headphones during study, lectures, or group activities to manage their sensory environments. Headphones, particularly modern smart and noise-cancelling models, can provide rich streams of data such as ambient noise levels, user volume preferences, listening patterns, microphone input, and contextual metadata (e.g., location of use, duration of listening). These data can be … Read more
This project will be in the area of Explainable AI (XAI), and specifically building of explanations to support learning and user interfaces for presenting explanations to the end user (learner). The focus will be on the explanations rather than machine learning technology, although the student can use the project as an opportunity to explore these … Read more
Risk detection models (such as IBM’s Granite Guardian) are increasingly used to flag harmful prompts and responses in large language model pipelines. These systems are trained on human and synthetic data to identify risks across multiple dimensions, but their reliability and fairness are not guaranteed. They may over-flag certain groups, miss subtle harms, or be … Read more
This project investigates how post-hoc counterfactual explanations can be used to debug opaque models such as deep neural networks by revealing which feature changes most influence predictions. In applications like anomaly detection, counterfactuals help clarify why certain cases are flagged as abnormal and expose when models rely on spurious correlations or biased patterns. By using … Read more