Computing Seminars – Spring 2025

The School of Computing at The University of Buckingham organises weekly Computing Seminars each academic term. These feature presentations by external experts, as well as contributions from the school’s academics and research students. The seminars offer a platform for sharing technologies and research, fostering collaboration, discussion, and intellectual exchange. Open to all Computing students, they form a key part of the school’s research environment.

The Spring Seminar series began in Week 4 with a presentation by PhD student Saleh Al Hashmi, who explored the link between sentiment analysis and cybersecurity threat intelligence. By analysing tweets in English and Arabic from the X platform, he developed a real-time framework detecting correlations between public sentiment and cyberattacks. Using machine learning, the system achieved strong classification accuracy, showing how spikes in negative sentiment can lead to cyber threats. His talk encouraged discussion and highlighted the power of AI in digital security.

In Week 5, MSc Computing (by Research) student Kalthum Mohammed presented her project, “Chronic Disease Prediction in Smartwatches using Machine Learning Algorithms.” Using data from wearable sensors, her system predicts chronic conditions like diabetes and cardiovascular disease, offering personalised health advice through a recommendation engine. The session showed how wearable tech and AI can transform healthcare with data-driven insights.

Week 6 welcomed guest speaker Dr Ali Al-Sherbaz, a University of Buckingham alumnus and Assistant Professor in Digital Skills at the University of Cambridge. His talk, “AI-Powered Innovation in Cybersecurity,” addressed ethical challenges such as bias in AI systems.

Drawing from his work with Cambridge Medical School, he discussed how training datasets can be biased, and how user-defined standards and customised GPT models help promote fairness. His presentation provided a critical perspective on responsible AI development.

In Week 7, PhD candidate Ethan Caldeira presented research on brain imaging for autism spectrum disorder (ASD) diagnosis. Using 3D convolutional neural networks, he compared stochastic parcellation and predefined atlases in fMRI analysis. His findings suggested data-driven approaches may improve classification, and he outlined plans for regression-based analysis to explore neurological traits further.

The series concluded with a workshop led by PhD candidates Madara Premawardhana and Rashmi Perera: “How to Manage a Research Project.” They covered organising, conducting, and disseminating research, stressing skills like self-discipline and creative problem-solving. Tools such as Jira, Mendeley, and Overleaf were recommended to support effective academic work.

The Spring Term seminar series concluded successfully, offering a blend of theory, application, and collaboration. These sessions remain a cornerstone of the school’s academic culture, encouraging discovery and innovation. As the Summer Term nears, the Computing community looks forward to more inspiring talks and technological exploration.