EPSRC FUNDED PROGRAMME hub@edgeaihub.co.uk +44 (191) 208 6000

Contact us

Video Library: Our Research

Our Resesarch

Edge-AI Mec+ 6G Driven Smart Robots in Disaster Management Scenarios

National Edge AI Hub Demos for the Visit from the Minister for Science, February 6th 2026

Professor Jose Maria Alcaraz Calero, Aston University, Edge-AI Mec+ 6G Driven Smart Robots in Disaster ...Management Scenarios

To learn more about the National Edge AI Hub, please see our website: https://edgeaihub.co.uk/

Follow our latest updates on Linkedin: https://www.linkedin.com/company/national-edge-artificial-intelligence-hub/Show More

Edge-AI Mec+ 6G Driven Smart Robots in Disaster Management Scenarios

Edge-AI Mec+ 6G Driven Smart Robots in Disaster Management Scenarios

National Edge AI Hub Demos for the Visit from the Minister for ...

EdgeAI-Enables Responsible Federated Learning for Skin Cancer Diagnostics

EdgeAI-Enables Responsible Federated Learning for Skin Cancer Diagnostics

National Edge AI Hub Demos for the Visit from the Minister for ...

Hybrid Monitoring Framework for Anomaly Detection in Smart Home IoT-Devices

Hybrid Monitoring Framework for Anomaly Detection in Smart Home IoT-Devices

National Edge AI Hub Demos for the Visit from the Minister for ...

DrownedDrones: Secure Federated Edge AI for Drones

DrownedDrones: Secure Federated Edge AI for Drones

National Edge AI Hub Demos for the Visit from the Minister for ...

National AI Safety Lab

National AI Safety Lab

National Edge AI Hub Demos for the Visit from the Minister for ...

Federated Learning Demo

Federated Learning Demo

National Edge AI Hub Demos for the Visit from the Minister for ...

EdgeAI-Enables Responsible Federated Learning for Skin Cancer DIagnostics

EdgeAI-Enables Responsible Federated Learning for Skin Cancer DIagnostics

National Edge AI Hub Demos for the Visit from the Minister for ...

Cyber Security Risks in Connected and Autonomous Vehicles-Experimental Demonstration

Cyber Security Risks in Connected and Autonomous Vehicles-Experimental Demonstration

National Edge AI Hub Demos for the Visit from the Minister for ...

Hybrid Monitoring Framework for Anomaly Detection in Smart Home IoT-Devices

Hybrid Monitoring Framework for Anomaly Detection in Smart Home IoT-Devices

National Edge AI Hub Demos for the Visit from the Minister for ...

Edge-AI Mec+ 6G Driven Smart Robots in Disaster Management Scenarios

Edge-AI Mec+ 6G Driven Smart Robots in Disaster Management Scenarios

National Edge AI Hub Demos for the Visit from the Minister for ...

Research Seminars

Mobile Edge Computing and its Application in Vehicular/AI Scenarios

National Edge AI Hub webinar series: Dr. Yilun Zhang from Swansea University, titled "Mobile Edge Computing and its Application in Vehicular/AI Scenarios," on February 12th, 2 PM GMT.

Abstract:

The rise of ...AI has introduced a wave of computation-intensive and delay-sensitive applications in the vehicular domain. These applications generate vast amounts of data that require low-latency processing, which poses a challenge for local on-board systems due to their limited computational capabilities. To address this, mobile edge computing (MEC) offers a promising solution by providing additional computational power with minimal processing delay, and can be integrated with federated learning to leverage distributed computing resources effectively.

This talk will explore key resource allocation challenges in MEC, highlighting the potential of MEC’s resource management to enhance the performance of AI-driven systems. As existing research concentrates on application-level resource allocation, future work should advance toward a higher-level integration that combines the resource management with the optimization of AI learning, enabling the development of more intelligent, efficient, and adaptive MEC systems.

Speaker Biography: Dr. Yilun Zhang is a postdoctoral researcher in the Computer Vision and Machine Learning group, Department of Computer Science, Swansea University. He earned his PhD under the supervision of Prof. Jiangzhou Wang at the University of Kent, UK. His research focuses on edge computing, wireless communication, distributed learning, and multi-robot learning.Show More

Mobile Edge Computing and its Application in Vehicular/AI Scenarios

Mobile Edge Computing and its Application in Vehicular/AI Scenarios

National Edge AI Hub webinar series: Dr. Yilun Zhang from Swansea ...

Service-Oriented Evolution of Modern AI

Service-Oriented Evolution of Modern AI

Service-Oriented Evolution of Modern AI, Zheng Li, Queen's University ...

Service-Oriented Evolution of Modern AI, Zheng Li, Queen's University Belfast, UK
The National Edge AI Hub Webinar Series
December 3rd, 2025

Abstract: It is well known that understanding the evolution of technologies and ...its cause is essential for more discoveries and innovations. In the Artificial Intelligence (AI) domain, it has also been identified that scrutinising the development context and path of AI will be able to help both academia and industry better understand the current AI limitations, reveal future AI trends, and facilitate AI/digital transformations. Given the dramatic boom of modern AI, this webinar tends to potentially unearth the evolution pattern along the recent three AI waves (namely predictive AI, generative AI and agentic AI), and accordingly to guide AI research and development to focus on the most promising directions. We employed analogical reasoning as the research method and referred to the existing software architectural styles to inspire our understanding of the architectural evolution of modern AI technologies. We see a service-oriented trend in modern AI’s working mechanisms, and the offering of AI power seems to be transiting from a heavyweight and monolithic paradigm to an organisational and collaborative paradigm with more and more specific separation of concerns. Following this service-oriented evolution trend, we borrow software architecture lessons and foresee opportunities to grow the current AI wave to a further height, e.g., standardising AI agent-friendly APIs and developing serverless AI agents. Ultimately, we draw tentative conclusions: What is happening in the AI domain has happened before in the software engineering domain. It is worth reusing software architecture knowledge to evolve the architecture of AI technologies.

About the Speaker: Zheng Li received his Ph.D. degree and M.Phil degree from the Australian National University (ANU) and the University of New South Wales (UNSW) respectively. During the same time, he was a graduate researcher with the Software Systems Research Group (SSRG) at National ICT Australia (NICTA). He is now a lecturer at the School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, UK. Previously, he was a tenured assistant professor at the Department of Computer Science, University of Concepción, Chile. Before that, he was a postdoc researcher with the Cloud Control group at Lund University, Sweden. He was also a visiting research fellow with Software Institute at Nanjing University, China. Before studying abroad, he had around four-year industrial experience in China after receiving his M.Sc.Eng. degree from Beijing University of Chemical Technology and the B.Eng. degree from Zhengzhou University. His research interests include big data analytics, edge/cloud computing, empirical software engineering, and performance engineering.Show More

Opportunities in On-Device Learning

Opportunities in On-Device Learning

Opportunities in On-Device Learning with Dr. Blesson Varghese, ...

Edge Computing for RF-based Human Sensing

Edge Computing for RF-based Human Sensing

National Edge AI Hub Webinar Series: Edge Computing for RF-based Human ...

National Edge AI Hub Webinar Series: Edge Computing for RF-based Human Sensing with Shuokang Huang from Imperial College London. His talk explores how edge computing and machine learning can enhance ...device-free RF sensing in IoT systems by extracting meaningful features from complex, interference-prone signals to improve detection accuracy and efficiency.

To learn more about the National Edge AI Hub, please see our website: https://edgeaihub.co.uk/

Follow our latest updates on Linkedin: https://www.linkedin.com/company/national-edge-artificial-intelligence-hub/

Abstract: In the Internet of Things (IoT), Radio Frequency (RF) sensing plays a crucial role by detecting objects/events with RF signals. One of the latest RF sensing approaches is device-free RF sensing which utilizes signals from existing edge devices (e.g., WiFi routers, mobile phones, smart watches). These edge devices were initially designed for wireless communication but not for sensing, so device-free RF sensing may fail to achieve satisfactory detection accuracy due to radio frequency interference (RFI). To improve the accuracy of device-free RF sensing, machine learning (ML) is a promising solution because ML can find approximately optimal solutions to the complex objectives of RF sensing, whose factors (e.g., frequency, signal-to-noise ratio) are too complicated to express with explicit mathematical formulations. To this end, we investigate edge computing to learn from the vast amounts of RF data (e.g., RF signals, channel states) and thereby extract informative features from overlapping signals, balancing sensing performance and communication overhead. Overall, our investigation not only poses new challenges for existing studies but also opens up new opportunities for future work.

About the Speaker: Shuokang Huang is a Ph.D. student supervised by Prof. Julie A. McCann in AESE Group, Department of Computing, Imperial College London. His research focuses on human sensing with WiFi channel state information (CSI), device-free radio frequency (RF) sensing, and applied machine learning on RF sensing. His previous experiences involve semi-supervised adversarial learning, federated learning, etc. In 2021, he received his M.Sc. degree in Computer Applied Technology from Peking University. In 2018, he obtained his B.Eng. degree in Electronic Information Science and Technology from Sun Yat-sen University.Show More

Advanced Network Technologies and Intelligent Computing 2024 Keynote

Advanced Network Technologies and Intelligent Computing 2024 Keynote

Advanced Network Technologies and Intelligent Computing 2024 Keynote: ...

Designing High-Performance and Scalable Middleware for the Modern HPC and AI Era

Designing High-Performance and Scalable Middleware for the Modern HPC and AI Era

DK Panda is a Professor and University Distinguished Scholar of ...

Introduction to Edge Intelligence

Introduction to Edge Intelligence

Introduction to Edge Intelligence by Lorenzo Carnevale To learn more ...

Introduction to Federated Learning

Introduction to Federated Learning

Introduction to Federated Learning by Lorenzo Carnevale. To learn more ...

Research Seminar: Enhancing Analytics Speed Across Edge and Cloud Computing

Research Seminar: Enhancing Analytics Speed Across Edge and Cloud Computing

Enhancing Analytics Speed Across Edge and Cloud Computing: Platform ...