Professor Haijiang Li is a Chair in BIM for Smart Engineering at Cardiff University's School of Engineering. His roles include leading the Computational Mechanics and Engineering AI Research Group, directing the BIM for Smart Engineering Centre, and overseeing the BIM MSc programme. He holds editorial roles for journals like Construction Innovation and Automation in Construction , and chairs the European Group of Intelligent Computing in Engineering (EG-ICE). Research focuses on smart computational engineering platforms integrating BIM, AI, and big data for sustainable infrastructure. Key areas include digital twins, disaster management, and resilient urban systems. He has secured £40M in research funding, including £9M as PI, and led over 70 research staff and students. Prof. Li is a Standards Committee Technical Executive at buildingSMART, driving international BIM standards. His work includes co-authoring a book on BIM standards across China, the US, and the UK. Awards include Fellowships from the British Computer Society (FBCS) and the Higher Education Academy (FHEA). His research outputs span over 250 publications, covering topics like AI-driven bridge maintenance, ontology-based decision-making, and energy-efficient urban systems. Collaborations with industry and global partners emphasize practical applications of BIM and smart technologies.
Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.
Emanuele (Manuel) Trucco is a Professor of Computing and holds the NRP Chair of Computational Vision in the School of Science and Engineering at the University of Dundee. He is also an Honorary Clinical Researcher at NHS Tayside and previously served as an Adjunct Professor at the Chinese Academy of Sciences (2018–2021). His research is centered on computational vision and medical image analysis, particularly in retinal imaging and its applications in systemic disease detection. PhD, Electronic Engineering, University of Genoa (1990) MSc, Electronic Engineering, University of Genoa (1984) Manuel Trucco's research focuses on computer vision and medical image analysis , with a strong emphasis on retinal image analysis for early detection of diseases such as diabetes, cardiovascular conditions, stroke, dementia, and neurodegenerative disorders. He co-directs the VAMPIRE (Vessel Assessment and Measurement Platform for Images of the Retina) initiative, a collaborative effort between the Universities of Dundee and Edinburgh. This platform enables automated, multi-modal analysis of retinal images and has been used in biomarker studies across the UK and internationally. His work integrates deep learning , artificial intelligence , and biomedical engineering to develop non-invasive, scalable diagnostic tools. Industrial collaborations include Canon Medical, OPTOS plc, NIDEK, and Epipole plc, while institutional partners include the Royal College of Ophthalmologists and the UK Biobank Eye and Vision Consortium. Recent publications highlight a strong trend in using AI and deep learning to extract clinical insights from retinal images, including predicting cardiovascular outcomes in diabetic patients, estimating biological age, and analyzing retinal vasculature changes under physiological stress. His work bridges computer science, ophthalmology, and public health, contributing to precision medicine and health equity. His scientific contributions have been recognized through fellowships: FRSA (Fellow of the Royal Society of Arts) FIAPR (Fellow of the International Association for Pattern Recognition) Trucco has led or co-led major research projects, including a £7M NIHR grant on precision medicine for diabetes (Dundee-Chennai), a £1.1M EPSRC grant on vascular dementia biomarkers (PI), the 3M-Euro ITN "REVAMMAD", and several PhD studentships sponsored by OPTOS, NIDEK, SINAPSE, and Toshiba. He has served on the organizing and program committees of major international conferences such as MICCAI and the European Conference on Computer Vision. He is a key member of the VAMPIRE research team and the UK Biobank Eye and Vision Consortium , contributing to large-scale data analysis efforts in vision and systemic disease. His work is at the forefront of AI-driven healthcare innovation, with real-world applications in early disease detection and personalized medicine.
Simon Spencer is a Professor of Statistics at the University of Warwick, affiliated with the Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER) and the Warwick Analytical Sciences Centre (WASC). His research focuses on Bayesian inference applied to epidemiology, stochastic epidemic models, and statistical methods for analytical science. He has held previous positions at the University of Nottingham and Massey University in New Zealand. His teaching includes advanced courses such as CH923: Statistics for Data Analysis , ST925: Graduate Topics in Statistics , and MA4M1/MA6M1: Epidemiology by Example . His research group currently includes PhD students Matthew Adeoye and Richard Haughey, and MSc students Olli Smith and Sangavi Pirabakaran. He collaborates extensively with global health institutions on projects addressing infectious disease modeling and public health policy. Spencer’s work bridges statistical methodology and real-world applications, with a focus on outbreak detection, model comparison, and the integration of geostatistical data with transmission models. His recent contributions include frameworks for lymphatic filariasis elimination projections and analyses of HIV transmission dynamics in Uganda. He actively contributes to interdisciplinary research in systems biology and analytical chemistry, leveraging advanced statistical techniques to address complex health challenges.
Dr Adelaide Marzano is a Lecturer at the School of Computing Engineering and the Built Environment, Edinburgh Napier University, and a Visiting Professor at Pentecost University, Ghana. Her research focuses on manufacturing systems, CAD integration, tolerance analysis, and educational technology. She actively contributes to the Centre for Engineering and Mathematical Modelling, examining topics such as digital twin simulations for industrial ergonomics and e-learning efficacy. She serves as a PhD External Examiner and is a member of the Institution of Mechanical Engineers. Affiliations: Edinburgh Napier University (Primary), Pentecost University (Visiting) Key Roles: PhD Examiner, Research Group Member (Centre for Engineering and Mathematical Modelling) Her research spans manufacturing processes, including tolerance-aware product development and virtual reality applications in aerospace training. Recent work includes optimizing distillery operations via digital twin frameworks and investigating student preferences for e-learning tools across UK and Portuguese institutions. She also collaborates with industries like COMAU on ergonomic work cell design. Her current PhD project supervision involves machining optimization of additively manufactured medical components, emphasizing interdisciplinary approaches to advance manufacturing precision and efficiency.
Dr. Aliyu Abubakar is a Lecturer in Computer Science at Teesside University's Department of Computing & Games. He holds a PhD in Computer Science from the University of Bradford (2023), an M.Sc. in Cyber Security (2015), and a B.Sc. in Computer Science from Gombe State University (2012). Prior to his current role, he was a Postdoctoral Research Associate at the University of Liverpool (2022–2024). His research focuses on deep learning applications in medical imaging, cybersecurity, and pattern recognition. He is a member of the Nigeria Computer Society (NCS) and the Cyber Security Experts Association of Nigeria (CSEAN). Education: B.Sc. Computer Science, Gombe State University (2008–2012) M.Sc. Cyber Security, University of Bradford (2014–2015) Ph.D. Computer Science, University of Bradford (2018–2022) Research Interests: Abubakar’s work spans medical image analysis (e.g., burns assessment, kidney transplantation viability, malaria detection), cybersecurity (deepfake detection, P2P network security), and electrical engineering (partial discharge analysis). His deep learning models address challenges in healthcare diagnostics and industrial safety. Recent studies include human deception detection via facial image comparison and automated liver viability assessment using pre-trained neural networks. Key Trends in Publications: His 2020–2024 articles emphasize cross-disciplinary applications of deep learning, particularly in healthcare and electrical systems. Collaborations span institutions like the University of Liverpool and NHS clinical partners, reflecting his commitment to translational research. Awards & Grants: While no specific awards are listed, his high citation counts (e.g., 32 citations for malaria detection work) highlight impactful contributions. Grants and funding details are not disclosed in the provided texts. Labs & Teams: Active collaborations with multidisciplinary teams in medical imaging and cybersecurity, as evidenced by co-authored papers with clinicians and electrical engineers.
Yichuang Sun is a Professor of Communications and Electronics at the University of Hertfordshire, leading the Communications and Intelligent Systems Research Group and the Electrical and Electronic Engineering Department. He holds a PhD from the University of York (1996) and has over 450 peer-reviewed publications, 5 authored books, and 40+ supervised PhD students. His research focuses on wireless communications (5G/6G, RIS-aided systems), RF/microwave circuits, neuromorphic computing, and machine learning applications. He serves as Editor or Guest Editor for 12+ IEEE/IET journals and chairs technical committees for IEEE conferences. Notably ranked in the World's Top 2% Scientists since 2019, he also advises global institutions like Oxford and the Royal Academy of Engineering. Education: PhD in Electronics, University of York, UK (1996) Research Interests: Wireless/Mobile Communications and Networks RF and Microelectronic Circuits Neuromorphic Computing and Machine Learning Memristor-based Systems Secure and Energy-Efficient Communications Grants & Projects (selected): Advanced mmWave MIMO 4D Radar for Traffic Detection (2024–2027) Wireless Power Transfer for Implantable Medical Devices (2023–2025) RFID System for Sample Management (2021–present) Labs/Teams: Leads the Communications and Intelligent Systems Research Group, collaborating on 6G, neuromorphic hardware, and IoT systems.
Dr. Terrence Perera is a Teaching Professor in the Operations Management and Decision Sciences (OMDS) department at the University of Sheffield's Management School. With over 30 years of experience in teaching, research, and consultancy, he specializes in computer modeling/simulation, operations management, and supply chain management. He leads modules such as 'The Intelligent Organisation,' 'Internationalisation Challenge,' and 'Business Intelligence' in undergraduate and MBA programs. His work integrating Qlik into teaching earned him the 2025 Qlik Education Ambassador title, while his Internationalisation Challenge module was shortlisted for a postgraduate employability award by AGCAS. Education: BSc and PhD qualifications. Research Interests: Focus on Industry 4.0 integration, simulation in healthcare (e.g., neonatal unit analysis), supply chain data management, and sustainability initiatives. He has secured five EPSRC grants and managed Knowledge Transfer Partnership projects with firms like BAE Systems and Siemens. Professional Recognition: Recipient of the 2025 Qlik Education Ambassador award and AGCAS shortlist. His consultancy spans sectors including healthcare, manufacturing, and logistics. Teaching & Advising: Supervises student dissertations, develops case studies from industry collaboration. His modules emphasize real-world applications of analytics and modern technologies. Grants & Projects: Five EPSRC grants, multiple KTP projects focused on manufacturing systems and ERP. Collaborations include Sheffield Children’s Hospital and Fosters Bakery.
Professor Yongmin Li is a Senior Member of the IEEE and Senior Fellow of the Higher Education Academy at the Department of Computer Science , Brunel University London , within the College of Engineering, Design and Physical Sciences . His work spans multiple domains including data science, artificial intelligence, medical imaging, and foveated rendering. He has consistently been ranked in the world's top 2% scientists by Elsevier's Standardized Citation Indicators since 2020. Research Interests include Data Science Medical Imaging Computer Vision Biomedical Engineering Natural Language Processing Set-Membership Filtering Scientific Awards include 1st Place, RETOUCH Challenge (Online), MICCAI 2023 2nd Place, FeTA Challenge, MICCAI 2022 Most Influential Paper over the Decade Award, MVA 2019 Best Paper Award, Bioimaging 2018 VC Prize, Brunel University 2015
Robert Manderson is a Senior Lecturer in the University of Roehampton Business School, specializing in information systems, project management, and business research. He holds a B.Sc., Dip.Sc., M.Sc., and is a Fellow of the Higher Education Academy and PRINCE2 Registered Practitioner. His career spans software engineering at BAE Systems and academic research roles at Lancaster University and Manchester University, funded by EPSRC and BT Plc. External Examiner roles at York Business School (2020–2024), Glyndwr University (2013–2016), and University of West London (2011–2015) Member of British Academy of Management and IEEE Research interests focus on ICT in business, Cloud computing, Big Data, education technology, and employability. He contributes to textbooks on Management Information Systems and regularly reviews conference papers. Current projects explore Fintech regulation, aerospace IT innovation, and social media's role in student employability. Key awards: Fellow of HEA, PRINCE2 Certifications Teaching areas include data analytics, PRINCE2/Agile methodologies, and Adobe Creative Cloud. He has advised on modules across computing and business programs, emphasizing ICT's role in organizational success.
Professor Aydin Nassehi is Head of the School of Electrical, Electronic and Mechanical Engineering at the University of Bristol, UK. He holds the academic rank of Professor of Production Systems and actively contributes to research in smart manufacturing, agent-based modeling, and digital twins. Research interests include AI integration in manufacturing, generative design, and systems optimization. He has collaborated extensively with Dr. Ben Hicks on projects like ProtoTwinning and Designing the Future , focusing on digital twin applications and transdisciplinary engineering. His scholarly output spans over 150 publications, with recent work emphasizing explainable AI, sustainability in food supply chains, and biomedical manufacturing innovations. Publications demonstrate expertise in machine learning, digital twin cost modeling, and additive manufacturing optimization. His projects have received funding from EPSRC and other academic institutions. Current research explores Industry 5.0 challenges, balancing automation with human-centric approaches, and advancing interoperability in cloud manufacturing environments.
Dr. Imran Ahmed serves as a Senior Lecturer in Artificial Intelligence at Anglia Ruskin University's Faculty of Science and Engineering, School of Computing and Information Science. With over 100 research publications exceeding 250 JCR impact factor and an h-index greater than 30, he represents a distinguished academic in computer science and engineering fields. Dr. Ahmed's research spans multiple domains of artificial intelligence, with particular expertise in machine learning, deep learning, computer vision, and data science. His work focuses on medical imaging applications including brain tumor detection, Covid-19 detection, pulmonary nodule classification, and liver lesion detection. He also pioneers research in surveillance systems, IoT-enabled environments, anomaly detection, and AI applications for sustainability in environmental monitoring and precision farming. His recent publications demonstrate a strong trend toward practical AI applications in healthcare, environmental sustainability, and intelligent transportation systems. The research shows increasing emphasis on explainable AI, edge computing implementations, and interdisciplinary approaches that bridge computer science with medical, environmental, and industrial applications. His work consistently addresses real-world challenges with innovative technical solutions. World's top 2% scientists by Stanford University (2021, 2022) Double Gold Medallist Certificate of merit for brain MRI analysis for tumor detection Numerous awards for teaching, research, and administrative excellence Dr. Ahmed supervises research across multiple domains including medical imaging, healthcare informatics, surveillance systems, environmental monitoring, agricultural technology, recommender systems, anomaly detection, cyber security, public health, urban planning, smart cities, augmented reality, and human-computer interaction. His research projects include Human Surveillance and Activity Recognition, Data Analytics during Covid-19, Sustainable Healthcare applications, Deep Learning in Medical Imaging, and Sustainable Environmental Control frameworks. As Principal Investigator, he has led multiple funded projects integrating IoT and AI technologies for practical applications. He is actively involved in organizing technical sessions and workshops for IEEE conferences, particularly focusing on cybersecurity issues of IoT in Ambient Intelligence environments, connected intelligence for IoT applications, and real-time data processing in industrial contexts. His professional memberships include Fellow of the Higher Education Academy, Senior Member of IEEE, Member of ACM Computer Society, and Senior Member of the Institute of Research Engineers and Doctors.
Dr Craig Boote is a Reader and Deputy Director of Postgraduate Research at Cardiff University's School of Optometry and Vision Sciences. With a distinguished career spanning over two decades, he has established himself as an expert in ocular biomechanics and structural biology. His research focuses on understanding the biophysical properties of corneal and scleral tissues and their role in vision and disease. Boote earned his BSc in Physics/Biochemistry (First Class Honors) from Keele University (1992-1995), followed by a PhD in Structural studies of DNA using diffraction and spectroscopic methods from the same institution (1995-1999). His academic journey continued with research positions at Cardiff University, progressing from Research Associate (1999-2001) to Senior Research Associate (2001-2011), Lecturer (2010-2014), and Senior Lecturer (2014-2020) before attaining his current position as Reader. Dr Boote's primary research interests center on the structural biology and biomechanics of ocular tissues, particularly the cornea and sclera. He investigates how the hierarchical organization of collagen and other extracellular matrix components governs corneal transparency and refractive function, and how these properties are compromised in diseases like keratoconus. His work also explores the role of scleral and optic nerve head micro-architecture in glaucoma pathogenesis, using elevated intraocular pressure as a key risk factor. By developing novel synchrotron x-ray scattering and laser scanning multiphoton imaging techniques, he quantifies tissue micro-architecture to build finite-element models that describe mechanical behavior under normal and pathological conditions. Analysis of Dr Boote's recent publications reveals a strong focus on corneal biomechanics, glaucoma research, and advanced imaging techniques. His work bridges fundamental structural biology with clinical applications, particularly in understanding corneal transparency mechanisms and developing therapeutic strategies for corneal diseases. A notable trend is the increasing integration of computational methods, machine learning, and artificial intelligence in ocular imaging and biomechanical modeling, reflecting the interdisciplinary nature of modern ophthalmic research. Dr Boote's scientific achievements have been recognized with numerous awards, including becoming a Fellow of the Royal Society of Biology (2022), Research Leave Fellowship from Cardiff University (2018), and the Research Merit Prize at the 5th World Corneal Congress (2005). He has also received visiting appointments at prestigious institutions including Newcastle Research & Innovation Institute and National University of Singapore. As Deputy Director of Postgraduate Research, Dr Boote actively supervises students, currently guiding Qian Ma and Xiaorui (Raya) Wang. His research has been supported by significant funding, including an NIH Project Grant as Principal Investigator (2016-2018), a Fight For Sight Project Grant (2012-2015), and contributions to a major MRC Programme Grant (2012-2017). He maintains active collaborations with leading researchers worldwide, including Dr Harry Quigley at Johns Hopkins University, Prof. Thao Nguyen, and researchers at Singapore Eye Research Institute. Dr Boote leads a research team that utilizes advanced x-ray scattering facilities and microscopic imaging modalities to investigate ocular tissue structure. His laboratory work integrates structural biology, biomechanics, and computational modeling to address fundamental questions about corneal transparency and glaucoma pathogenesis. The team collaborates with international partners across the US, Singapore, and Europe to translate basic science findings into potential clinical applications for corneal diseases and glaucoma.
Dr. Dele Owodunni is a Senior Lecturer in Mechanical Engineering and Programme Leader of the MSc Mechanical Engineering at the University of Chester. He specializes in Design and Manufacturing, focusing on socially-responsible computerization of engineering processes based on law-like principles. His research includes developing taxonomies for design shapes and advancing sustainable manufacturing practices. Dr. Owodunni has secured over £100,000 in UK funding for research and enterprise activities. His work emphasizes improving design for manufacturing (DFM) in aerospace contexts, defect data management, and energy efficiency in machining. He has supervised PhD students and contributed to collaborative knowledge-sharing frameworks in manufacturing. His research interests span feature recognition in CAD/CAM, process optimization, and sustainability. Notable contributions include frameworks for micro-blogging in knowledge sharing and energy-efficient machining strategies. He actively engages in enterprise activities and has over 15 years of experience in UK academia and industry.
Professor Fred Charles serves as Head of Department for Creative Technology at Bournemouth University, specializing in computational intelligence applied to simulated worlds. His expertise spans artificial intelligence, human-computer interaction, and interactive narrative systems, with significant contributions to virtual reality and brain-computer interface technologies. His research has led to award-winning interactive systems and numerous publications in top-tier conferences and journals. Education: PhD in Computer Science ("Intelligent Virtual Actors in Interactive Storytelling") Master's degree in Computer Aided Graphical Technology Applications BSc in Computer Science Professor Charles' research focuses on the intersection of AI, narrative systems, and immersive technologies. His work explores how computational intelligence can enhance virtual environments, particularly through brain-computer interfaces that enable more natural human-virtual agent interactions. Recent projects investigate social anxiety in VR settings, multimodal interaction frameworks, and personalized dialogue systems for virtual characters. His research bridges theoretical AI concepts with practical applications in healthcare, education, and entertainment domains. His most recent publications demonstrate a clear trend toward applying interactive narrative techniques to real-world problems, particularly in mental health assessment (OCD, social anxiety), responsible gambling initiatives, and educational applications. The work increasingly incorporates multimodal input analysis and neurofeedback mechanisms to create more responsive and adaptive virtual experiences. Scientific Awards: Blue Sky Award (ACM Hypertext, 2018) Best Application (International Conference on Automated Planning and Scheduling, 2013) Professor Charles has successfully supervised numerous PhD students working on topics ranging from crowd simulation to narrative generation systems. His research has been supported by substantial grants from Innovate UK, Economic and Social Research Council, AHRC/EPSRC, and the European Commission, including projects on believable agent behavior in VR, responsible online gambling, and machine understanding for interactive storytelling. He maintains active collaborations with researchers across Europe and has contributed significantly to the development of narrative medicine applications.
