Advanced Cloud

This involves designing and optimising distributed computing paradigms where processing occurs closer to the data source (at the "edge" of the network). The focus is on low-latency applications, real-time analytics, and seamless integration with centralised cloud resources to leverage the strengths of both environments.

This area is dedicated to improving the efficiency and performance of computing systems across various levels, from hardware architecture to software algorithms. Research often involves resource management, parallel processing, energy efficiency, and developing methodologies to maximise computational throughput and minimise overhead.

This focuses on advancing artificial intelligence capabilities and the underlying hardware/software systems that accelerate AI workloads. It encompasses research in machine learning algorithms, deep learning, neural networks, and leveraging specialised hardware (like GPUs, TPUs, FPGAs) to drastically speed up AI model training and inference.

This area centres on the challenges and opportunities presented by massive datasets. Research here includes developing novel techniques for data collection, storage, processing, and analysis, with a focus on extracting meaningful insights, patterns, and predictions from complex and high-volume information.

This combines two critical and evolving fields. Cybersecurity research focuses on advanced threats, secure systems design, cryptography, and privacy preservation in digital environments. Quantum Computing explores the fundamental principles of quantum mechanics to develop new computing paradigms with the potential to solve problems intractable for classical computers, including breaking current cryptographic standards and enabling new forms of secure communication.