Alison Varey is a Senior Lecturer at the School of Computing, Edinburgh Napier University , with a focus on computing education , student identity , and transitions from further to higher education . She contributes to research on graduate apprenticeships , sociability in online communities , and participatory research methods like photovoice. Research Areas: Student transitions, identity formation, work-integrated learning, digital skills gaps Projects: Associate Student Project (ASP), Graduate Apprenticeship studies Collaborators: Debbie Meharg, Ella Taylor-Smith, Sandra Cairncross, Sally Smith Her recent work examines hybrid professional identities and motivational factors in apprenticeships . She has secured funding from Skills Development Scotland and the Scottish Funding Council . Key publications include studies on student identity formation via photovoice and work-study balance in graduate apprenticeships. Advising: Supervised the thesis "A journey that motivates": Discovering the associate student experience (2015-2022).
Dr. Shaojun Feng is an Honorary Principal (Professorial) Research Fellow at the Centre for Transport Studies within the Department of Civil and Environmental Engineering, Faculty of Engineering, Imperial College London. He is a leading expert in Global Navigation Satellite Systems (GNSS), with over thirty years of research experience focusing on GNSS integrity, high-accuracy positioning, augmentation systems, and functional safety for autonomous and safety-critical applications. His research interests span a wide range of topics including GNSS integrity monitoring, precise point positioning (PPP), real-time kinematic (RTK), ionospheric modeling, spoofing detection, software-defined receivers, and integrated navigation systems. He has made pioneering contributions to the development of GNSS correction services with integrity, enabling lane-level navigation in smartphones and certified use in autonomous vehicles. His work bridges theoretical advances with real-world deployment, notably through a commercial service benefiting over 1.5 billion users. The recent publications highlight a strong focus on ionospheric modeling and correction using machine learning (e.g., LSTM, ConvLSTM), sparse reconstruction techniques in tomography, and integrity-aware positioning for autonomous systems. There is a clear trend toward integrating AI with GNSS, improving real-time accuracy, and ensuring safety through robust integrity monitoring—especially in multi-constellation environments (GPS, Galileo, BeiDou). Dr. Feng has been recognized with several prestigious honors: Michael Richey Medal, Royal Institute of Navigation ESA certification for leading Galileo receiver development Recognition by UK Space Agency for UK leadership in Galileo adoption SGS certification for safety-critical GNSS correction service He is actively involved in the academic and standards communities, serving as Associate Editor for the Journal of Navigation and GPS Solutions , and as Chairman of WG3 in RTCM Special Committee 134, which develops international standards for GNSS integrity monitoring. He is a Chartered Engineer (CEng) and Fellow of both the Institution of Engineering and Technology (FIET) and the Royal Institute of Navigation (FRIN), the latter presented by HRH Prince Philip. His leadership in research, editorial roles, and standardization underscores his significant impact on the field of navigation and positioning. Dr. Feng leads research initiatives at Imperial College London with strong industry and agency collaborations, including with the European Space Agency and SGS. His work on integrity-certified GNSS services represents a major advancement in positioning for autonomous systems, with implications for future smart mobility, transportation safety, and resilient navigation infrastructure.
Sir Andy Hopper is a Professor and Head of the Digital Technology Group within the Computer Laboratory at the University of Cambridge. He is a Fellow of Corpus Christi College, Cambridge. His research focuses on creating a world where everything is always connected in a personalized way and developing sentient computing systems that observe the real world to ensure planetary sustainability. His research interests span ubiquitous computing, sentient computing, distributed systems, computer networking, green computing, and provenance systems. He has pioneered work in location-aware systems, energy-efficient computing, and provenance in distributed environments. His vision extends computing to automatically adapt to real-world conditions for sustainable solutions. Recent publications indicate a strong focus on provenance systems, data reliability in cloud environments, and the integration of renewable energy in datacentre computing. His work often involves collaboration with researchers at the University of Cambridge and beyond, addressing challenges in virtualization, MapReduce, and resource accounting. Professor Hopper leads the Digital Technology Group, which is part of the Computer Laboratory. The group conducts cutting-edge research in networking, systems, and sustainable computing, contributing to both theoretical advances and practical applications in the field.
Dr. Sergio Maffeis is an Associate Professor and Senior Lecturer in Computer Security at the Department of Computing, Imperial College London, within the Faculty of Engineering. He leads the Security & Machine Learning Lab and holds affiliations with the Engineering Secure Software Systems and Programming Languages research groups. His research focuses on cyber security, machine learning, formal methods, and programming languages. Maffeis earned his Ph.D. from Imperial College London and an MSc from the University of Pisa, Italy. Research interests include adversarial machine learning, intrusion detection systems, and secure software development. His work bridges theoretical foundations with practical applications, such as detecting Advanced Persistent Threats (APTs) and improving ML model robustness against adversarial attacks. Recent publications highlight advancements in combining machine learning with security, including KnowML for knowledge graph-enhanced ML-NIDS and APIRL for REST API fuzzing. He has supervised numerous PhD students, including Abdullah Aldaihan (Large Language Models for Cyber Threat Detection) and Fahad Alotaibi (Concept Drift in ML-based Security). Grants include EPSRC/GCHQ funding for certified verification of client-side web programs and GCHQ grants for web security and lab infrastructure. His lab collaborates on projects like the Security & Machine Learning Lab, exploring cutting-edge topics in secure AI and network defense.
Ahmad Fahim Habib is a Research Fellow in the Department of Physics at the Faculty of Science, University of Strathclyde, United Kingdom. He is actively engaged in advanced research in plasma-based particle acceleration and free-electron lasers, with a focus on achieving ultrahigh 6D brightness electron beams. He is affiliated with major international collaborations, including SLAC National Accelerator Laboratory and the EuPRAXIA project. Research Fellow, Department of Physics, University of Strathclyde Visiting Researcher, SLAC National Accelerator Laboratory (2024) Member, Collaboration Board – EuPRAXIA Preparatory Phase (2024) Principal Investigator and Co-investigator on multiple funded research projects His research interests lie at the intersection of plasma physics and accelerator science. He specializes in developing novel techniques for generating and accelerating high-brightness electron beams using plasma wakefield and hybrid acceleration schemes. His work aims to enable next-generation free-electron lasers with attosecond and Ångstrom-scale resolution, which could revolutionize ultrafast science and imaging. Key areas include plasma photocathodes, energy spread compensation, beam brightness optimization, and staging of plasma accelerators. He leverages high-performance computing and experimental collaborations to validate theoretical models. The recent publications of Ahmad Fahim Habib reflect a strong trend toward advancing the performance limits of plasma-based accelerators, particularly in achieving cold, high-brightness electron beams for free-electron laser applications. His work spans experimental, theoretical, and computational domains, with a focus on overcoming key challenges such as energy spread, emittance, and beam stability. The recurring themes across his articles include brightness enhancement, photocathode development, energy compensation techniques, and hybrid acceleration schemes, all aimed at making plasma accelerators viable for future light sources. Scientific Awards: Saltire Emerging Researcher Award (2021) APS DPP Travel Award (2017) DAAD FIT Worldwide Scholarship (2015) Ahmad Fahim Habib has been actively involved in securing research funding and leading projects. He served as Principal Investigator for the 'Ultra-high brightness beams from hybrids plasma accelerators' project funded by the SUPA Saltire Emerging Researcher Award (2022), and is currently a Co-investigator on the DOE-funded 'High-gradient acceleration of electrons in plasma and dielectric structures' (2024–2026). He has also participated in the Doctoral Training Partnership at the University of Strathclyde (2016–2024), supporting PhD research. He is accepting PhD students and has supervised doctoral work, including his own thesis completed in 2024. He is actively involved in experimental and theoretical research groups focused on plasma accelerators. He collaborates with leading teams at SLAC, EuPRAXIA, and the University of Strathclyde’s plasma physics group. His work is part of a broader effort to develop compact, high-performance particle accelerators for scientific, medical, and industrial applications.
Professor Jonathan Pritchard is the Judith and Harold Rosenberg Chair in Quantum Computing and an RAEng Senior Research Fellow at the University of Strathclyde, where he is Head of the Experimental Quantum Optics and Photonics Group within the Department of Physics, Faculty of Science. His research is centered on developing scalable neutral atom quantum computing platforms and quantum sensing technologies. His research focuses on neutral atom quantum computing , quantum LIDAR , and quantum sensing using Rydberg atoms . His group pioneered the UK’s first scalable neutral atom quantum computing platform through the SQuAre EPSRC Prosperity Partnership with M Squared Lasers, achieving fault-tolerant single-qubit gate operations on up to 225 qubits. Current work includes developing a cryogenic dual-species system for quantum error correction. His team’s research has led to the commercial Maxwell platform. Recent publications (2024–2025) highlight advancements in quantum metrology with entangled spin systems, graph optimization on Rydberg arrays, and quantum-enhanced, jamming-resistant rangefinding. These works reflect a strong trend in applying quantum control techniques to practical quantum computing and sensing applications. RAEng Senior Research Fellowship (2023) Quantum Technology Fellowship (2015) Jonathan Pritchard leads multiple funded research projects, including the Hub for Quantum Computing via Integrated and Interconnected Implementations (QC13) and a studentship on error-correction in neutral atom systems. He supervises PhD students and is actively involved in professional service, including invited talks, conference organization, peer review, and external PhD examinations. He leads the Experimental Quantum Optics and Photonics Group, which is at the forefront of quantum technology development in the UK, with strong industry collaboration through M Squared Lasers.
Muhammad Aaqib is a Doctor of Philosophy and Research Associate at the School of Computing , affiliated with the Faculty of Computing, Engineering and Built Environment . His work focuses on trust management in Internet of Things (IoT) systems, leveraging machine learning and deep learning methodologies. Education : Doctor of Philosophy (PhD) Research Interests : Internet of Things (IoT) Security Trust Management Systems Machine Learning and Deep Learning Models Explainable Artificial Intelligence for IoT Ensemble Learning Techniques Scientific Awards : Prize for Discriminative features-based trustworthiness prediction in IoT devices using machine learning models (2023)
Dr. Shitharth Selvarajan is a Lecturer in Cyber Security at Leeds Beckett University, affiliated with the School of Built Environment, Engineering and Computing. He holds a PhD in Computer Science & Engineering from Anna University and completed postdoctoral research at the University of Essex, UK. With over seven years of teaching experience, he is an active researcher and educator in digital and network security domains. His research focuses on Cyber Security, Blockchain, Critical Infrastructure, SCADA systems, Network Security, and Ethical Hacking . He has contributed significantly to the field through over 100 international journal publications and 20 conference presentations. His doctoral work centered on SCADA network security, a critical component of industrial infrastructure protection. Dr. Selvarajan has secured and contributed to multiple funded research projects from international bodies, including the Ministry of Education in Ethiopia and Saudi Arabia. He holds four published patents in intellectual property rights and is a recognized expert in blockchain technologies, being a certified Hyperledger expert and blockchain developer. He is an active member of several professional organizations, including: IEEE Computer Society International Blockchain Organization And four other professional bodies He serves as a reviewer and editor for numerous international journals published by IEEE, ACM, Elsevier, Springer, IET, Wiley, MDPI, Hindawi, and others. His current teaching responsibilities include: Ethical Hacking and Penetration Testing (Level 4) Web and Network Security (Level 5) Digital Security (Level 6)
Dr. Tingting Li is a Lecturer (Assistant Professor) in Cyber Security at Cardiff University's School of Computing and Informatics and a member of the Centre for Cyber Security Research. She also holds an Honorary Research Fellow position at Imperial College London, reflecting her ongoing research collaboration. Her work bridges artificial intelligence and cybersecurity, with a focus on protecting critical systems such as cyber-physical systems (CPS), industrial control systems (ICS/SCADA), and autonomous vehicles. BEng (Hons) in Information Security, Xidian University, China MSc in Computing, Imperial College London PhD in Artificial Intelligence, University of Bath Dr. Li’s research interests lie at the intersection of AI and cybersecurity, particularly in automated cyber defense , diversification/deception strategies , and symbolic AI for knowledge representation . She investigates how AI can enhance the resilience of critical infrastructures through intelligent, adaptive defense mechanisms. Her recent work explores quantum-inspired reinforcement learning and machine learning models for proactive threat mitigation in complex systems. Her recent publications demonstrate a strong trend in applying advanced AI techniques—especially deep reinforcement learning, LSTM networks, and Bayesian models—to cybersecurity challenges in industrial and autonomous systems. These works span domains like IoT malware suppression, network diversity for ICS resilience, and automated compliance checking, reflecting a multidisciplinary approach combining security, AI, and systems engineering. Dr. Li has secured significant research funding, including a grant from the Alan Turing Institute (2024–2025) on AI safety in autonomous cyber defense, a RITICS/NCSC-funded project on diversity-based cybersecurity (2021–2022), and an EPSRC-funded project on metric-driven cybersecurity frameworks for critical national infrastructure (2021–2023). She actively supervises PhD students in areas including cybersecurity for autonomous vehicles, moving target defense, and cyber-physical system security. Her team includes Iryna Bernyk, Sanyam Vyas, Victoria Marcinkiewicz, Ellis Doran, Stephen Morris, and Sam Braithwaite. She also leads teaching modules on databases (CM6125/CM6625) and cybersecurity (CM6224/CM6724). Dr. Li’s research is conducted within the Centre for Cyber Security Research at Cardiff University, where she collaborates with experts in AI, security, and critical infrastructure protection. Her work is highly interdisciplinary, involving partnerships with institutions like Imperial College London and funding bodies such as EPSRC, NCSC, and the Alan Turing Institute.
Dr Stace Constantinou is a Senior Lecturer in Popular Music and Programme Leader for the Popular Music course at the University of Northampton, affiliated with the Centre for Cultural and Literary Studies within the Culture school. He holds a PhD from Kingston University and is actively engaged in creative research, supervision, and public engagement. PhD, Processes of creative patterning: a compositional approach, Kingston University (2015) His research centers on the intersection of music, technology, and artificial intelligence. He explores AI through programmatic electronic music, develops analytical tools for popular song, and investigates the adaptation of mathematical symmetry into digital signal processing. His creative work emphasizes spatial sound, immersive performance, and the materiality of the audio-object within DAW environments. Key themes include musical creativity, novelty, patterns, and the philosophical implications of AI in music. His recent creative outputs form a thematic arc exploring AI, rebellion, and human identity, most notably through The SAPIAN Trilogy and Rebel-Misfit . These works blend electronic composition with narrative depth, often inspired by thinkers like Zylinska, Bostrom, and Kurzweil. His publications and compositions reflect a consistent focus on sound as a medium for knowledge exchange and conceptual exploration. His scientific recognition includes the Ricordi Prize for Best Composition and the Schillinger Composition Prize. Ricordi Prize for Best Composition Schillinger Composition Prize He supervises two practice-based PhD students: Gemma Boaden, exploring hybrid voice practices for actors, and Michael W. Bell, researching experiential soundtracks using spatial audio technologies. He has secured internal funding for the LIPSY: Live Immersive Performance Soundscape project (2024–2025), demonstrating active grant involvement. His work extends to public engagement through podcasts, radio programs, and exhibitions with the Royal Society of Arts. Dr Constantinou is actively involved in a creative research lab focused on immersive and spatial sound, leading the LIPSY project. His work is inherently collaborative, involving partnerships with artists, film directors, and institutions like Resonance FM, Angel Studios, and The Podcast Company.
Dr. Abdulghani A. Ahmed is a Senior Lecturer in Digital Forensics and Course Leader for MSc Cybersecurity at the School of Computer Science and Informatics, De Montfort University (DMU), UK. He is affiliated with the Cyber Technology Institute (CTI) and has a long-standing academic career since 2004, previously serving as a Senior Lecturer at University Malaysia Pahang. University: De Montfort University School: School of Computer Science and Informatics Role: Senior Lecturer, Course Leader (MSc Cybersecurity) Email: aa.ahmed@dmu.ac.uk ORCID: 0000-0001-9748-6067 Education: PhD in Network Security & Intrusion Detection Systems, Universiti Sains Malaysia (2014) MSc in Network Forensics & Identity Spoofing Investigation, Al-Neelain University (2006) BSc (Hons) in Computer Science, Sudan University of Science and Technology (2002) Dr. Ahmed’s research focuses on critical areas in cybersecurity, including digital forensics, IoT authentication, big data privacy, cloud and network security, malware analysis, incident response, and cybercrime investigation. His work integrates machine learning, bio-inspired algorithms, and proactive forensic models to enhance cyber resilience. He has led numerous research projects and published extensively in top-tier journals such as IEEE Access, Sensors, and Springer. The recent publications reflect a strong trend toward digital forensics in cloud and mobile environments, bio-inspired security frameworks, and machine learning applications in cybercrime detection. His work bridges theoretical innovation and practical deployment, particularly in real-time intrusion detection and evidence collection. Scientific Awards and Honors: Multiple Gold, Silver, and Bronze medals from international innovation exhibitions (MTE2018, Citrex, iCAN, ICE-CINNO) CENDEKIA BITARA AWARD 2016 for high-impact journal publication Nominated for Best PhD Thesis Award at USM (2015) Three-time High Impact Publication Award (2011–2013) at USM Dr. Ahmed actively supervises PhD students and has secured significant research funding as Principal Investigator from Innovate UK, COMSTECH-TWAS, and Malaysian government grants. His consultancy work includes cybercrime investigation and incident response for SysArmy Sdn Bhd and Golden Carousel Sdn. Bhd. He is a Senior Member of IEEE and IAENG, and holds professional certifications including SFHEA (UK), Cellebrite CCO, and digital forensics credentials from AccessData and Condition Zebra. He leads the Cyber Technology Institute research group at DMU, focusing on next-generation cybersecurity solutions. His projects include proactive forensic models, IoT security frameworks, and AI-driven botnet detection systems, positioning him at the forefront of applied cybersecurity research.
Professor Jerry Knox is a leading academic in Agricultural Water Management at the Cranfield Water Science Institute, Cranfield University. He holds the rank of Professor and is actively engaged in research, consultancy, and project leadership in water resources, irrigation, and climate resilience in agriculture. Research Interests: Agricultural water management and irrigation systems Climate change impacts and adaptation in farming Biophysical and water resource modeling Drought resilience and risk management Sustainable food production and net zero agriculture Water-energy-food-environment (WEFE) nexus His recent publications (2022–2024) reflect a strong focus on modeling climate impacts, developing decision support tools (e.g., D-Risk), promoting sustainable irrigation, and addressing water scarcity in both temperate and tropical regions. These works span disciplines including environmental science, agronomy, hydrology, and policy, with a geographic scope covering the UK, Africa, South America, and South Asia. Scientific Contributions: Principal Investigator on multiple high-impact projects funded by FCDO, Innovate UK, Defra, and British Council Author of over 100 peer-reviewed journal papers Google Scholar h-index: 40; Scopus h-index: 31 Developed tools for drought risk assessment and irrigation planning Advising and Funding: He leads and co-leads multiple research grants focusing on climate resilience, irrigation innovation (e.g., floatovoltaics), and sustainable agrifood systems. While specific students are not listed, his collaborative publications suggest active mentorship and research leadership. Labs and Teams: Jerry Knox is affiliated with the Cranfield Water Science Institute and contributes to research communities such as 'Water for Food in a Changing Climate' and 'Resource Recovery'. He collaborates with industry partners (e.g., Dyson Farming, Berryworld) and NGOs, integrating academic research with real-world applications.
Alan Mills is a Lecturer in the Department of Computer Science and Creative Technologies at the University of the West of England (UWE Bristol). His research focuses on containerization , malware analysis , offensive security , and the application of machine learning and visualization to cybersecurity. He specializes in cybersecurity pedagogy and teaches Computer and Network Security on UWE's Cyber Security MSc program. His expertise extends to outreach initiatives like the CyberWEST project, aimed at upskilling teachers in the South West region, and leading funded research projects on cybersecurity education. Outside academia, he works as a cybersecurity engineer developing secure video communication solutions.
Dr. Gabriel Wallin is an Assistant Professor in Statistics at the School of Mathematical Sciences, Lancaster University. Previously, he held postdoctoral positions at Inria and a Research Fellow role at the London School of Economics and Political Science, where he was supervised by Dr. Yunxiao Chen and Professor Irini Moustaki. His academic journey began with a PhD from Umeå University in 2020 under Professor Marie Wiberg. Education: PhD in Statistics, Umeå University (2020) Supervisor: Marie Wiberg Dr. Wallin's research bridges latent variable modeling and statistical learning, focusing on fairness and interpretability in social, behavioral, and health sciences. Key areas include structural learning of latent models, multivariate outlier detection, model-based clustering, algorithmic fairness in education, and change-point detection for latent factors. His methodology development addresses test score equating, robustness analysis, and sparse loadings in factor models. Recent publications highlight trends in propensity score methods for test equating (2025), latent change-point modeling for educational assessment (2025), and sparse rotation techniques for exploratory factor analysis (2023). Collaborative work spans educational testing, psychometrics, and social data science. Scientific Awards: Best Reviewer Award, Psychometric Society (2025) ODA Early Career International Fellowship (2024) Dr. Wallin supervises PhD student Yawen Ma and actively collaborates with researchers like Yunxiao Chen and Marie Wiberg. He has secured grants from EPSRC, Duolingo, and the ODA, with recent projects on test security and fairness in digital learning environments. His service roles include co-editing Psychometric Society proceedings and associate editorships at Teaching Mathematics and its Applications .
Hamza Shakeel serves as Associate Professor (Reader) at Queen's University Belfast within the School of Electronics, Electrical Engineering and Computer Science. He holds affiliations with the Material and Advanced Technologies for Healthcare Institute and Energy Power and Intelligent Control research group, maintaining an active laboratory in Ashby Tower (Room 07.010). His work bridges semiconductor manufacturing, MEMS development, and environmental sensing technologies. Research focuses on microelectromechanical systems for precision sensing applications, particularly MEMS-based chemical sensors, microfluidics, and functional nanomaterials. Key specializations include lab-on-a-chip devices, micro-gas chromatography systems, quartz crystal microbalance sensors, and MEMS oscillators for gas/liquid analysis. Current projects emphasize greenhouse gas monitoring, microbial volatile collection, and advanced semiconductor manufacturing techniques using 3D printing. Recent publications demonstrate convergence of MEMS sensor innovation with AI-driven edge computing for environmental monitoring. Work spans materials science (fused silica resonators), analytical chemistry (photoionization detectors), and microfabrication techniques, showing consistent output in high-impact journals and conferences since 2011 with accelerating productivity through 2025. Scientific recognition includes: 3rd Prize Poster Presentation at Graduate Research Symposium, Blacksburg (2014) Early Career Travel Grant (2019) Secured research funding includes 6 active projects as PI/CoI, notably the National Edge AI Hub for cyber-disturbance analysis and MISO observatory for greenhouse gas monitoring across extreme environments. Supervised 3 research students with ongoing PhD recruitment in semiconductor and glass manufacturing. Laboratory resources include Agilent Gas Chromatography System, SRS QCM instrumentation, Laser Doppler Vibrometer, and specialized microfabrication equipment supporting sensor development from design through field deployment.
