School of Computer Science and Statistics
Current communication between devices and cloud infrastructure is based largely on IPv4 or IPv6. Information-Centric Networking (ICN) proposes to retrieve information from the ‘network’ based on named content instead of focussing on communication with a endpoints identified by addresses. ICN approaches such as Named-Data Networking (NDN) require consumers to express interests for individual chunks of … Read more
Learning a second language is a challenging and time-consuming task. While a myriad of strategies have been proposed, we are still far from reaching an optimal personalised solution. Users either drop out early in the process or, once they reach a sufficient level of proficiency, they hit a plateau that seems impossible to overcome. This … Read more
In the era of large-scale communication networks, understanding user mobility patterns is crucial for optimizing network resources, improving service quality, and enhancing user experience. Mobility models provide insights into how users move within a network, influencing network planning, resource allocation, and handover decisions. However, traditional approaches to identifying these models often rely on predefined assumptions … Read more
The growing complexity of communication networks, especially with the introduction of 5G and future 6G, requires new approaches to ensure that these networks can meet the increasing demands for low latency, high reliability, and efficient resource allocation. Traditional centralized control methods often struggle to cope with the dynamic nature of these networks, particularly in environments … Read more
Speeches by charismatic and not so charismatic politicians can sometimes create unexpected and revolutionary changes in nation states. Charismatic politicians can convey sentiments by a subtle choice of words – the so called emotion laden words and ordinary words- can precipitate major socio-political changes. In political debates the politicians use words that may discredit their … Read more
This project will deal with recognition of facial emotion recognition using generative models and comapring the results of GenAI models with key industry standard machine learning models. You will be building a transformer for facial emotion recognition – broadly expressions of happiness, anger, surprise, contempt, and sadness– and for recognising head movements – upward/downward, sideways, … Read more
The advent of IoT devices led to the creation of many different, distributed machine learning techniques to identify patterns and make logical decisions based on the large volumes of data generated. Traditionally, these devices readily shared their raw data with a centralised server. However, this sharing of raw data is not conducive to maintaining the … Read more
Auditory communication has a central role in our society. However, it remains unclear how our brains allow us to understand complex sounds, such as speech and music. The use of machine learning methods to study neural data has recently led to a major paradigm shift, greatly advancing our understanding of auditory perception. The Di Liberto … Read more
https://github.com/mathworks/MATLAB-Simulink-Challenge-Project-Hub/tree/main/projects/Wind%20Turbine%20Predictive%20Maintenance%20Using%20Machine%20Learning
I supervise projects in the areas of Serious Games and Interactive Digital Narrative (IDN). Games have become an important cultural form, which has been shown also to hold great potential for other purposes than entertainment, such as learning and cultural engagement. Serious Games research is concerned with how such game experiences are designed, implemented and … Read more