Honours and Masters project

In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed infrastructures, improving system performance, scalability, and efficiency by optimizing resource usage (e.g., GPUs, CPUs, energy consumption).

In SmartScaleSys (S3), we aim to design and build resource management solutions to learn from usage patterns, predict future needs, and allocate resources to minimize latency, energy consumption, and costs of running diverse applications in large-scale distributed systems. This project offers researchers and students a chance to explore cutting-edge concepts in AI-driven infrastructure management, distributed computing, and energy-aware computing, preparing them for impactful roles in industry and research.

This project will involve benchmarking state of the art methods for time series classification on the new MONSTER benchmark datasets [1, 2, 3].  Currently almost all benchmarking in time series classification is performed on the (almost all very small) datasets in the UCR and UEA archives.  This is particularly unsuitable for deep learning models which are low bias models and ideally trained using large quantities of data.  The "true" performance of current deep learning methods for time series classification is unknown outside of the UCR/UEA datasets.  Most deep learning models for times…

Politeness plays a pivotal role in fostering constructive, respectful communication and maintaining positive social dynamics in educational settings. In online learning environments—such as discussion forums on Moodle—language becomes the primary medium for interaction between instructors and students. While prior studies have highlighted the benefits of politeness in building rapport and encouraging engagement, limited empirical work has systematically examined how politeness is expressed by both instructors and students in these digital spaces.

Are you interested in biomedical? You could combine your data science and computing expertise to analyse DNA and genetics.

Do you play any classical music instruments, like piano or violin? Would you like to combine your advanced music skills with computer science. This project analyses classical music using computer science techniques.
 

Do you play any classical music instruments, like piano or violin? Would you like to combine your advanced music skills with computer science. This project analyses classical music using computer science techniques.

Are you interested in applying your AI/DL knowledge to the medical domain?

Are you interested in programming maps, such as GoogleMaps or Open Street Maps? This project uses online maps extensively for visualising routes, and other objects of interest.