Queen’s University Belfast is leading research that makes Artificial Intelligence (AI) faster, more efficient, and more secure by moving it closer to where data is generated, i.e., to the edge.
Through advances in hardware acceleration, edge computing, and embedded AI systems, Queen’s researchers are designing intelligent, low-power solutions that are beginning to transform how and, more importantly where, industries from healthcare to manufacturing are analysing their data, thereby allowing better real-time performance.
This research, developed across the School of Electronics, Electrical Engineering and Computer Science (EEECS) and led by experts including Professor Roger Woods, is delivering global impact through partnerships with major international research institutions, e.g., Tyndall National Institute, multinational companies such as AMD, Seagate, SAP, spin-outs such as Analytics Engines Ltd, in the creation of next-generation edge AI solutions.
Research Challenge
Bringing AI Out of the Cloud
AI is changing every aspect of society, but traditional cloud-based systems struggle to meet the growing demands for speed, energy efficiency, and privacy.
For industries such as healthcare, telecoms, key infrastructure or autonomous manufacturing, who handle massive levels of data or sensitive information, sending every piece of information to a remote server is now too slow, energy-intensive, and insecure.
Queen’s researchers set out to solve this challenge by embedding AI capability directly into devices, sensors, and edge networks where are the data is captured, so that it can be analysed, learned from, and acted upon in real time.
Making Hardware Smarter
Bringing intelligence to the edge requires rethinking computer architecture. State-of-the-art Field-Programmable Gate Arrays (FPGAs) offer huge potential for accelerating AI. However, the complexity of designing and optimising systems for AI workloads has traditionally been a major barrier for their adoption by industry.
Our Approach
Integrating AI with Hardware and Embedded Systems
Researchers at Queen’s, including Professor Roger Woods, have pioneered hardware and software co-design methods that enable AI and data analytics to run efficiently on embedded devices, such as FPGAs.
His group’s research has focused on pioneering edge computing for AI and machine learning. Key innovations include: supporting local inference without relying on a high dependency on cloud processing; adjusting the precision of the computing needed depending on the application needs, thus saving energy; and creating novel design techniques that allow complex analytics to be deployed rapidly on programmable hardware.
These methods directly informed the creation of Analytics Engines Ltd, a Queen’s spin-out company who have now gone on to deliver accelerated data-analytics solutions to global clients such as Artemis, RTE, Seagate and Agri-food and Biosciences Institute.
Cross-University Collaboration in AI Innovation
Queen’s is advancing AI through interdisciplinary collaboration across the university. The i-AMS Centre (Intelligent Autonomous Manufacturing Systems) applies AI and machine learning to robotics, industrial control, and sensor systems. The Centre for Secure Information Technologies (CSIT) integrates AI into next-generation cybersecurity solutions. The Kelvin-2 High-Performance Computing Facility, led by Professor Roger Woods, provides powerful infrastructure for supporting a range of AI research across Queen’s.
Queen’s is also a key partner in the Alan Turing Institute’s Network Development Awards and the Centre for Doctoral Training in Future Open Secure Networks (FORT), training the next generation of AI and secure-systems researchers.
“Queen’s research is enabling AI to work faster, smarter, and closer to the source of data, transforming how industry and society harness intelligence in real time.”
- Professor Roger Woods
What impact did it make?
Turning Research into Real-World Solutions
The research behind Analytics Engines has been translated into commercial products that dramatically speed up data processing. They transform businesses with a comprehensive approach that combines customisable AI services with powerful software accelerators to unlock the full potential of a company’s data.
Boosting the Digital Economy
Analytics Engines has created highly skilled jobs in Northern Ireland, attracted over £1 million in early investment, and supported the digital transformation of more than 30 organisations across healthcare, finance, and digital infrastructure. They organise Ireland’s leading data and AI annual conference, Big Data Belfast, which bring together 800+ thought leaders, industry experts, and data-driven innovators from across the UK, Ireland and beyond.
Powering a Sustainable Future
By embedding AI directly into devices and optimising precision, Queen’s researchers are helping reduce the carbon footprint of data processing and data centres. Their designs enable significant energy savings while maintaining performance, advancing sustainable computing in line with global climate targets.
Securing the Next Generation of AI
Queen’s AI research is contributing to making digital systems safer and more trustworthy. Through the FORT Doctoral Training Centre and collaborations within Secure Connected Intelligence, researchers are developing AI-driven cybersecurity and privacy-preserving edge networks that are critical to the future of digital trust.
Our impact
Impact related to the UN Sustainable Development Goals
Learn more about Queen’s University’s commitment to nurturing a culture of sustainability and achieving the Sustainable Development Goals (SDGs) through research and education.
