Computing, Cybersecurity, Mathematics, and Informatics

IMPACT

By focusing on practical, real-world applications, we develop advanced solutions to address critical issues, such as improving public safety, enhancing healthcare outcomes, and transforming industries with data analysis and AI-driven insights.

COLLABORATIONS AND PARTNERSHIPS

We partner with a wide range of industries to deliver innovative solutions which address business needs, foster economic growth, and support the development of key sectors. By collaborating with organisations across healthcare, cybersecurity, digital technologies, and manufacturing, we ensure our research has a tangible impact.

These partnerships not only enhance our research capabilities but also provide valuable opportunities for knowledge exchange, technology transfer, and the co-development of cutting-edge products and services that drive industry advancements.

• Aneurin Bevan University Health Board
• Cardiff and Vale University Health Board
• Cwm Taf Morgannwg University Health Board
• Cyber Wales
• DVLA
• Powys Teaching Health Board
• South Wales Police
• Sport Wales
• Tarian RCCU (Regional Cyber Crime Unit)
• Thales Ltd
• Welsh Government
• Wales Institute of Digital Information (WIDI)
• Goggleminds

FACILITIES

National Cyber Security Academy

Located at the Newport Campus, the National Cyber Security Academy spans two floors dedicated to cyber security education and applied research. The space is designed to support collaborative projects between academia, industry, and government.

Secure Operations Centre (SOC)

The Secure Operations Centre provides a controlled environment for research on security operations, mirroring the infrastructure and practices used in industry. It enables studies on threat detection, incident management, and system resilience.

Digital Investigation Lab

This lab is equipped for research into digital forensics, offering tools and systems comparable to those used by law enforcement and corporate investigators. It supports studies in data recovery, evidence analysis, and cybercrime investigation techniques.

Crime Scene House

The Crime Scene House facilitates research on forensic methods in simulated crime environments. Scenarios range from domestic burglaries to complex cases such as homicides and arson, offering opportunities to study evidence collection and analysis in realistic conditions.

Hydra Simulation Suite

The Hydra suite supports research on incident response and decision-making during cyber-attacks. It enables controlled simulations to analyse behaviours, evaluate response strategies, and develop protocols for improving organisational resilience.

Industrial Control Lab

The Industrial Control Lab enables comprehensive testing of cyber governance and penetration strategies within simulated factory environments. This hands-on facility supports practical industrial work by recreating real-world operational scenarios, allowing researchers and practitioners to refine security measures, identify vulnerabilities, and enhance system resilience. Through targeted simulations and rigorous evaluations, the lab drives innovation in securing industrial operations against emerging cyber threats.

Research-informed teaching

At USW, research-led teaching integrates the latest developments from our own research into computing degrees, ensuring that students gain direct exposure to pioneering work in artificial intelligence (AI), software development, and cybersecurity. This approach connects students with the very best research being conducted by our researchers, providing them with cutting-edge knowledge and practical applications that are immediately relevant to their future careers.

In the MSc Artificial Intelligence, students study modules on machine learning and deep learning, informed by our research in intelligent fraud dedication, cancer diagnosis, and text summarisation and generation. In the BSc Applied Cybersecurity, students learn about network security and IoT vulnerability assessments, linked to our ongoing research in cloud service identification and intrusion detection systems. Hands-on labs using real-world data sets and security challenges allow students to apply this research to practical situations.

By connecting students with our research, they gain up-to-date, industry-relevant skills that prepare them for careers in technology. This ensures our graduates are equipped with the knowledge to tackle real-world challenges in AI, cybersecurity, and beyond.

Research students

Ramadhan Rajab is a PhD student in Cybersecurity/AI.

“My PhD is developing a security framework for the Internet-of-Medical-Things (IoMT). IoMT refers to the use of mobile computing, medical sensors, and cloud computing to monitor patients' vital signs in real-time and the use of communication technologies to relay data to a cloud computing framework. The data can be accessed by physicians to monitor, diagnose, and treat patients effectively.

"IoT security is critical in order to protect the vast amount of data they handle from cyber-attacks. The ultimate goal is that, by protecting the system, we protect patients’ lives."

Nigerian-born Dr Mitchell Eboigbe completed a PhD in Geoinformatics.

"My PhD has significantly enhanced my skills and employability. It has provided me with in-depth analytical expertise in digital photogrammetry and computing. I can now develop innovative techniques for data collection and analysis, which are highly valued in industry and essential for research.

“I chose to study at USW because of its renowned GIS and computing team. USW has a strong research ranking in the UK and consistently high student satisfaction. The university offers a welcoming and supportive environment, which made me feel at home. I initially came to pursue a Masters in GIS and decided to stay on for my PhD.

"I've found the Welsh people to be warm and welcoming, and there is a strong university community that both my family and I truly appreciate."

Nick Andrews Data Science PhD

Nick Andrew's Data Science PhD focuses on hallucinations in Large Language Models (LLMs), where inaccurate or fictional information is generated, posing challenges in applications such as mental health care. The research aims to create a new metric to predict and identify hallucinations in LLMs, using a mix of quantitative and qualitative analyses. This work can help enhance the accuracy of LLMs for practical use.