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Algorithms are at the heart of all information-processing and research in this field emphasises mathematical technique and rigour. Our group designs and analyses algorithms in terms of resource requirements (time, space, randomness) and studies their limitations.

Working to develop computational and analytical tools to support collective and cooperative decision making using a blend of game theory, AI (artificial intelligence), and algorithms, the Algorithmic Decision Theory Group collaborates on fundamental optimisation problems.

Technology's impact on education is vast, with the research field aiming to explore computing education research, learning sciences, educational research, and educational psychology. The Computing and Engineering Group’s research aims to encompass a broad range of these research subfields to align with the CSE's range of expertise.

Developing advanced computational methods for automated image analysis and downstream data analytics, the Computer Vision Group employs methods that are based on solid mathematical and statistical modelling, as well as data-driven artificial intelligence using machine and deep learning.

A world leader in database, data management, and (big) data analytics, the work of The Data and Knowledge Research Group accelerates data-intensive applications, and supports insightful knowledge-extraction from large-scale, complex and dynamic real-life datasets.

Much of the technology we use each day is controlled by embedded systems, but as our needs and demands change, so does the technology and systems which control them. We look at ways to improve these systems and innovate new technologies which have a positive impact on the community.

The Formal Methods Group works on the foundations of computation, developing logical and probabilistic frameworks for areas of computer science encompassing imperative and logical programming, concurrent and distributed computing, computer security and artificial intelligence.

In the Human-Centred Computing (HCC) group, our goal is to build and design technologies which understand people, respond to their needs adaptively, and improve their experience. The advancement of human-computer interfaces and ubiquitous computing are changing the world, bridging the gap between our physical and digital worlds.

A fundamental assumption in Knowledge Representation and Reasoning is that an agent's knowledge is explicitly represented in a declarative form, suitable for processing by dedicated reasoning engines. The assumption that much of what an agent deals with is knowledge-based, is common in many modern intelligent systems.

With interests in all aspects of machine learning, the research remit of the Machine Learning Group is broad. The group looks into various application domains, including bioinformatics, biomedical image analysis, cybersecurity, human-computer interaction, robotics and recommender systems.

Developing novel concepts, methods, tools, and technology, the Networking and Ubiquitous Computing research group works to investigate the ubiquitous connectivity and sensing underpinning smart environments.

Cognitive Robotics concerns the use of Artificial Intelligence methods to allow an autonomous system to learn and reason about its environment and how to behave appropriately to achieve its goals.

Founded on the area of service-oriented computing, the Software Engineering group investigates a paradigm which is now embedded in many other computing disciplines, and which underpins several research and solution design approaches.

Focusing on the design, implementation and verification of real-world software systems that are safe and secure in the strongest sense – that of mathematical proof – the Trustworthy Systems Group’s activities range from fundamental research, to the creation of technology and its transfer to the real world.