The UK National Edge AI Hub is delighted to open the call for nominations for the 2026 Awards for Excellence and Impact in Edge AI. These prestigious awards honour individuals who have made outstanding, field-shaping contributions to Edge Artificial Intelligence, from pioneering tools and techniques to driving breakthroughs across sectors such as healthcare, transport, and manufacturing. Celebrating achievement at every career stage, the awards spotlight innovation, inspire future advances, and showcase the transformative power of Edge AI.
In 2026, the National Edge AI Hub Awards for Excellence and Impact in Edge AI will be conferred and presented during the IoT 2026 Conference (17–20 November 2026), providing awardees with international recognition at one of the leading global forums for research and innovation in the Internet of Things and Edge AI. Award recipients will also be recognised through the National Edge AI Hub Annual Meetup, extending visibility across the UK’s leading Edge AI research and innovation ecosystem. The National Edge AI Hub brings together a leading UK innovation ecosystem comprising the UK’s top 15 universities and a network of more than 80 industry partners, creating a unique platform for collaboration between academia and industry. The awards are judged by an eminent international panel of researchers and practitioners, including fellows of prestigious societies, leaders of major national programmes, and experts with proven industrial impact. Recognition through the IoT 2026 Conference and the National Edge AI Hub Annual Meetup will provide awardees with exceptional visibility among world-class researchers, technology leaders, investors, and policymakers, highlighting the National Edge AI Awards as a prestigious benchmark for excellence and innovation in Edge AI.
Awards and Presentation
Award Categories
Distinguished Technical Achievement Award (Senior Researcher)
This award recognises a senior researcher (12+ years post-PhD) who has demonstrated sustained leadership and made ground-breaking contributions to the field of Edge AI. The nominee should have an established track record of high-impact research, active mentorship, and leadership in collaborative and cross-disciplinary initiatives. A maximum of one individual will be selected for this award.
Applications for the Distinguished Technical Achievement Award (Senior Researcher) will be assessed against five key criteria. Candidates should provide clear evidence of these in their CV, nomination letter, and reference letter. Assessment will consider:
- Research excellence and impact: demonstrated through influential publications, citation impact, best paper awards, featured papers in leading journals, and broader recognition within the Edge AI community.
- Leadership and innovation: evidenced by leading major research projects, shaping emerging research directions, and delivering impact in industry or practice.
- Mentorship and capacity building: demonstrated through the successful supervision, development, and support of early-career researchers and students.
- Collaboration and interdisciplinarity: reflected in partnerships and research activities spanning disciplines, sectors, institutions, or countries.
- Service and community contributions: including editorial responsibilities, conference leadership, professional service, and engagement with the wider research community.
Rising Star Award (Postdoctoral / Early Career Researcher)
This award recognises an early-career researcher or postdoctoral researcher (5-12 years post-PhD) who has demonstrated exceptional promise and innovation in Edge AI. The nominee should have made original research contributions and shown strong potential for significant future impact in the field. Up to three individuals will be selected for this award.
Applications for the Rising Star Award (Postdoctoral / Early Career Researcher) will be assessed against four key criteria. Applicants should provide evidence of these in their CV, nomination letter, and reference letters. Assessment will consider:
- Originality and quality of research: demonstrated through innovative contributions to Edge AI and early evidence of independent research leadership.
- Research impact and recognition: shown through high-quality publications, awards, citations, or other indicators of influence within the field.
- Collaboration and engagement: reflected in contributions to collaborative and interdisciplinary projects, as well as active participation in the research community.
- Future potential: evidenced by a clear trajectory towards becoming a leading researcher in Edge AI.
Future Star Award (PhD)
This award recognises outstanding PhD research that demonstrates exceptional originality, technical excellence, and innovation in Edge AI. Nominees must have completed their PhD within the past five years and produced research that makes a significant contribution to the field, with clear potential for lasting impact across domains such as healthcare, transport, and manufacturing. Up to three awardees will be selected in this category.
Applications for the Future Star Award (PhD) will be assessed against four concise criteria. Applicants should provide evidence of these in their CV, thesis abstract or summary, nomination letter, and reference letters. Assessment will consider:
- Future potential: demonstrated through early recognition, publications, awards, or other indicators of a promising research career.
- Originality and innovation: demonstrated through novel ideas, methodologies, or findings that advance the state of the art in Edge AI.
- Technical excellence and rigour: reflected in the quality, depth, and methodological soundness of the research.
- Impact and significance: evidenced by the contribution of the thesis to advancing Edge AI research or its applications in areas such as healthcare, transport, and manufacturing.
Nominations
A candidate may be nominated by a member of the research or professional community. An individual may nominate at most one candidate per award category. Self-nominations are not eligible. Nominations should be submitted as one PDF document via email to awards@edgeaihub.co.uk.
Each nomination must be submitted as a single PDF file (the PDF should be named lastname-awardcategory-2026) and include the following:
- Name and email of the nominator;
- Name and email of the nominee;
- A nomination statement (maximum 500 words) explaining why the nominee is deserving of the award, with emphasis on relevance to Edge AI and alignment with the award category;
- A current CV of the nominee (maximum four pages);
- Up to two letters of support (i.e. reference letters) from individuals other than the nominator. These should be collected by the nominator and included in the PDF submission. Members of the selection committee may not serve as nominators or referees.
Important Dates
- Nomination Deadline: 15 September 2026
- Notification of Results: October 2026
Award Selection Committee
Prof. Rajiv Ranjan (Chair)
National Director, UK Edge AI Hub
Fellow of IEEE and Academy of Europe
Newcastle University, UK
Prof. Albert Zomaya
Fellow of IEEE, Academy of Europe, and Australian Academy of Science
The University of Sydney, Australia
Prof. Prem Prakash Jayaraman
Director, Factory of the Future and Digital Innovation Lab
Swinburne University of Technology, Australia
Prof. Liana Cipcigan
Fellow of the Learned Society of Wales
Cardiff University, UK
Prof. Massimo Villari
University of Messina, Italy
Mark Goh Voon Wei
Senior Manager, iTrust Cybersecurity Centre
Singapore University of Technology and Design, Singapore
Award and Presentation
Awardees will receive a commemorative plaque and formal recognition through the National Edge AI Hub website, communications channels, and promotional activities associated with the 2026 IoT Conference.
The awards will be presented during a dedicated awards session at IoT 2026, offering recipients the opportunity to be recognised among leading international researchers, industry innovators, and policymakers. Through both the National Edge AI Hub and the 2026 IoT Conference, awardees will benefit from enhanced visibility and a high-profile platform that showcases their achievements and impact within the global Edge AI and Internet of Things communities.
The 2025 Edge AI Hub Awards are now officially closed, and we are delighted to announce this year’s outstanding recipients.
These prestigious awards honour individuals who have made outstanding, field shaping contributions to Edge Artificial Intelligence — from pioneering tools and techniques to driving breakthroughs across sectors such as healthcare, transport, and manufacturing. Celebrating achievement at every career stage, the awards spotlight innovation, inspire future advances, and showcase the transformative power of Edge AI.
The Rising Star Award celebrates emerging leaders who are making exceptional contributions to secure and scalable Edge AI innovation, and this year’s winners:
Professor Dongxiao Yu
Shandong University
In recognition of his pivotal contributions to efficient and cyber-resilient collaborative learning in Edge scenarios for supporting real-time and safety-critical applications.
Read more about Professor Yu’s research here.
Professor Zhenyu Wen
Zhejiang University of Technology
In recognition of his outstanding research and significant contributions that advance the deployment of AI algorithms in resource-constrained environments such as the Internet-of-Things and Edge Computing.
Read more about Professor Wen’s research here.
Dr Wei Li
University of Sydney
For his pioneering work on translating novel Edge AI algorithms into sustainable, real-world systems to address global challenges like energy management for net-zero buildings and early disease detection in healthcare.
Read more about Dr Li’s research here.
The Future Star Award, recognising early‑career researchers demonstrating remarkable promise and impact, has been awarded to:
Dr Yuewei Wang
China University of Geosciences
For advancing environmental and urban risk prediction and emergency response through the innovative integration of digital-Earth concepts, geoscientific models, and Edge Computing to develop digital-twin emergency framework.
Read more about Dr Wang’s research here.
Dr Debin Liu
Huazhong University of Science and Technology
In recognition of his outstanding work on developing effective techniques for deploying high-performance AI models on resource-constrained Edge devices.
Read more about Dr Liu’s research here.
Dr Ayman Ibrahim Noor
Taibah University
In recognition of his innovative work on integration of Cloud, Edge, and Microservices paradigms to enable intelligent, autonomic Edge AI monitoring frameworks, laying the foundation for next-generation smart environments.
Read more about Dr Noor’s research here.
We extend our warmest congratulations to all six awardees for their achievements and their continued contributions to advancing the field of Edge AI.