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
I am happy to supervise final-year undergraduate projects and master’s theses (Data Science). Below are the research topics. As these topics rely on advanced mathematical and statistical methods, only candidates with a strong background in mathematics or statistics will be considered. I also welcome PhD enquiries. If you’re interested, please contact me to discuss your … Read more
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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
Students in higher education frequently face challenges with sensory processing that can impact their ability to focus, engage, and collaborate. These challenges include sensory overload (e.g., from noisy lecture halls or crowded group settings), under-stimulation (e.g., fatigue, low arousal), and distraction (e.g., constant notifications). Addressing these issues is essential for fostering inclusive learning environments. Smart … Read more
Mobile phones are ubiquitous in higher education and are already integrated into students’ daily routines. Beyond their role in communication, they provide a rich source of sensor data (e.g., microphone, accelerometer, gyroscope, screen interaction patterns, GPS, app usage). These data streams can act as proxies for environmental conditions (e.g., noise, movement, crowding) and user states … Read more