Find Academic Supervisors

• Health Policy and Systems Research
• Social Determinants of Health
• Participatory Action Research
• +9 more

Dr. Lucia D'Ambruoso is a Senior Lecturer at the Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen. She is based at the Aberdeen Centre for Health Data Science and leads international research on health systems, participatory methods, and verbal autopsy. She holds honorary and visiting positions at the University of the Witwatersrand (South Africa), Umeå University (Sweden), and Stellenbosch University, and serves on multiple international research and policy committees. PhD in Public Health, University of Aberdeen (2011) MSc in Public Health and Health Services Research, University of Aberdeen (2003) BSc (Hons) in Pharmacology, University of Aberdeen (1997) Her research focuses on health policy and systems, social determinants of health, and participatory action research, especially in sub-Saharan Africa and South Asia. She uses qualitative and mixed methods to understand how health systems can be made more equitable and responsive through community engagement, inter-sectoral action, and innovative data systems like verbal autopsy. Her recent publications demonstrate a strong focus on community-led health research, digital health platforms for emergency care, school-based mental health, and mortality data systems. She leads major NIHR and GCRF-funded programmes in South Africa and Rwanda, aiming to strengthen primary care and injury response systems through participatory methods. Scientific Awards: University of Aberdeen Interdisciplinary Research Award (2024) University of Aberdeen Outstanding Research Award (2024) Fellow, Stellenbosch Institute of Advanced Study (2025) Fellow, Royal Society for Public Health (2021) Fellow, Higher Education Academy (2017) Dr. D'Ambruoso teaches across global health, health policy, and research methods at both undergraduate and postgraduate levels. She supervises PhD students and is Deputy Director of the Centre for Global Development at the University of Aberdeen. She is actively involved in community engagement through NHS Grampian and serves on the editorial board of Global Health Action and the Steering Committee of the Politics of Health Group. Her research is supported by NIHR, MRC, Wellcome Trust, and international philanthropies. She leads the Verbal Autopsy with Participatory Action Research (VAPAR) initiative, which connects communities, researchers, and policymakers to generate actionable evidence on health equity. Her team works closely with the Agincourt HDSS in South Africa and has developed innovative tools for community health worker training and data collection.

John ClarkView profile

Professor

• Cybersecurity
• Software Engineering
• Artificial Intelligence
• +5 more

John Clark is a Professor of Computer and Information Security at the University of Sheffield since 2017 and Director of the Siemens Digital MINE. Previously, he held roles as Professor of Critical Systems at the University of York (1992–2017) and worked at Logica in security R&D. He studied Mathematics and Applied Statistics at the University of Oxford. His research focuses on cybersecurity, software engineering, and AI applications, particularly in threat modeling, intrusion detection, quantum cryptanalysis, and secure autonomous systems. Clark leads the Security of Advanced Systems research group and has secured grants totaling over £36 million. Notable projects include the EPSRC-funded DAASE (2012–2019) and the Active Building Centre (2018–2022). His work on phishing detection (e.g., analyzing user behavior) and malware analysis has been widely recognized. He has been awarded the Royal Society Wolfson Merit Award (2013), GEECO medals (2005, 2013), and multiple best-paper prizes. Clark’s research spans theoretical and applied domains, including evolutionary computation for cryptanalysis, robotic system security, and smart grid protection. His labs explore areas like digital twin authentication and privacy-aware energy theft detection. He has supervised numerous grants and maintains active collaborations with industry and academia.

Thomas KjeldsenView profile

Professor

• Extreme events
• Machine learning
• Hydrological modelling
• +2 more

Thomas Kjeldsen is a Professor in the Department of Architecture & Civil Engineering at the University of Bath. He leads multiple research projects funded by organizations such as The British Council, Royal Academy of Engineering, and The Leverhulme Trust. His research focuses on extreme events, machine learning, hydrological modeling, and nature-based solutions. He is affiliated with centers including the Water Innovation and Research Centre (WIRC), EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa), and the Institute for Mathematical Innovation (IMI). Research Interests: Extreme events, machine learning applications in hydrology, flood risk management, and civil engineering resilience. Key Projects: Development of rainfall frequency models for infrastructure design, flood reconstruction using historical data, and capacity-building for South African flood studies. His work contributes to UN Sustainable Development Goals related to climate action and clean water. Recent studies emphasize non-stationary hydrological analysis, urban flood modeling using machine learning, and interdisciplinary approaches to water resource management. Activities include advising doctoral students, organizing academic events (e.g., British Hydrological Society Symposium), and serving on external committees like Affinity Water. His research has been widely cited and featured in policy discussions and international media.

• Architecture
• Urban and regional planning
• Design
• +5 more

Professor Alan Penn is a leading academic at University College London's The Bartlett School of Architecture , where he holds the title of Professor in Architectural and Urban Computing. He previously served as Dean of the Bartlett Faculty of the Built Environment from 2009 to 2019 and has been instrumental in establishing Space Syntax Ltd , a UCL knowledge transfer spin-out company. His affiliations include membership in the Space Syntax Laboratory, board membership of UCL Consultants Ltd, and trustee status at Shakespeare North Trust. Education: BSc (1978), Dip Arch (1980), MSc (1983) - all from University College London Alan Penn’s research investigates how spatial design influences social and economic behaviors through innovative space syntax methodologies . Key areas include: Agent-based simulations of human behavior Spatio-temporal representations of built environments Urban spatial network analysis Urban sustainability across multiple dimensions Cognitive markers in architectural design Historical urban growth modeling His recent publications demonstrate a strong focus on computational urbanism, evolutionary city patterns, and behavioral architecture. Research trends show interdisciplinary approaches combining architectural theory with: Machine learning applications Network science analysis Behavioral psychology insights Historical GIS techniques Complex systems modeling Public health considerations Scientific recognition includes: HEFCE Business Fellowship (2001-2005) KTP SE Region Award (2010) Multiple UCL Enterprise awards ‘Spirit of Enterprise’ Award (2008) As Principal Investigator he leads the £5m EPSRC-funded Urban Dynamics Lab , demonstrating sustained research excellence. His work extends to public engagement through: Shakespeare North Trust educational theatre development Media appearances (New Scientist, Slashdot) Public policy contributions

Ahmad LotfiView profile

Professor

• Computational Intelligence
• Ambient Intelligence
• Robotics
• +7 more

Ahmad Lotfi is a Professor of Computational Intelligence and Head of Department of Computer Science at Nottingham Trent University , with a Visiting Professor role at Tokyo Metropolitan University . He leads the Computational Intelligence and Applications (CIA) research group and has supervised over 30 PhD students to completion. PhD in Learning Fuzzy Systems (University of Queensland, 1995) MTech in Control Systems (Indian Institute of Technology, India) BSc in Control Systems (Isfahan University of Technology, Iran) His research spans computational intelligence , ambient intelligence , robotics , and machine learning , with applications in dementia monitoring , smart environments , and healthcare technology . Recent work focuses on using thermal sensor arrays for privacy-preserving human activity analysis. He has secured funding from Innovate UK , EPSRC , The Royal Society , and Horizon 2020 , with projects like iCarer (assistive living), SmartBerry (agricultural AI), and BigSpark (financial data augmentation). His 15 most recent articles demonstrate expertise in Wi-Fi-based activity recognition , EEG fall detection , and thermal sensor fusion . Senior Member IEEE Member of British Computer Society (MBCS) Editorial roles in Soft Computing and Journal of Ambient Intelligence and Smart Environments He has served as Program Chair for conferences like PETRA and ICCRT , and as Keynote Speaker at PETRA 2023 . His 28+ years of academic leadership include organizing UKCI and UKRAS conferences.

Haydar AygunView profile

Associate Professor

• Acoustic Materials
• Metamaterials
• Biomedical Acoustics
• +7 more

Dr. Haydar Aygun serves as Associate Professor in Acoustics and Building Services at the Bioscience and Bioengineering Research Centre, Department of Civil and Building Services Engineering, University of Salford. He holds multiple leadership roles including Course Director for the MSc Environmental and Architectural Acoustics, Diploma in Acoustics and Noise Control, and The Acoustics Apprenticeship programs. With a PhD in Acoustics and Vibration from the University of Hull (2006), his academic foundation includes a MSc in Advanced Materials, Processes and Manufacturing (2002) and a BSc in Mechanical Engineering. Dr. Aygun's research spans multiple critical domains of acoustics: Development and characterization of novel acoustic materials and metamaterials for noise control Duct acoustics and sound propagation through complex media Biomedical applications including bone analysis and respiratory sound detection Vibration control of porous materials using advanced computational methods Environmental noise assessment and building acoustics solutions His publication record shows consistent scholarly output with 46 research items from 2006-2025, demonstrating particular productivity in recent years (7 publications in 2023). His work shows increasing integration of computational methods with experimental validation, expanding applications in medical diagnostics and sustainable building technologies. Dr. Aygun actively contributes to the academic community through multiple service roles: Editorial Board Member for Journal of Applied Acoustics EPSRC Grant Reviewer Reviewer for Journal of Applied Acoustics and Journal of the Acoustical Society of America Deputy leader of Biomedical Acoustics Special Interest Group within UK Acoustics Network As an educator, Dr. Aygun has supervised numerous PhD students and teaches across multiple levels from undergraduate Building Services Engineering to specialized postgraduate Acoustics programs. His consultancy work bridges academic expertise with practical industry applications in noise assessment, building acoustics, and event sound management.

Evina KatsouView profile

Visiting Professor

• Sustainable resource recovery from wastewater
• Circular economy assessment
• Data analytics for environmental systems
• +5 more

Dr Evina Katsou is a Visiting Professor in the Department of Mechanical and Aerospace Engineering within the College of Engineering, Design and Physical Sciences at Brunel University London. She serves as Course Director for the Water Engineering MSc program and leads the Water & Environmental Engineering research group with 20 researchers. Dr Katsou's educational background includes a PhD in 'Wastewater Treatment with the Use of Membranes' (2008-2011), an MSc in Water Resources Science & Technology (2006-2008), and an MEng in Chemical Engineering (2000-2005), all from the National Technical University of Athens (NTUA), Greece. Her research program focuses on three interconnected areas: (1) Sustainable resource recovery from wastewater and safe reuse; (2) Data analytics, knowledge discovery and process modelling; and (3) Circularity & sustainability measurement and assessment. Dr Katsou has developed innovative approaches for biological nutrient removal from wastewater, including partial nitrification/denitrification and complete autotrophic nitrogen removal processes. Her work integrates advanced data analytics methods such as multivariate statistics, clustering techniques, machine learning algorithms, and artificial neural networks to identify complex relationships between process variables, particularly for measuring GHG emissions in water treatment systems. Dr Katsou has authored 98 journal publications (h-index: 27) and 12 book chapters with over 100 presentations, and holds a patent on biopolymers recovery. Her recent publications demonstrate a strong focus on circular economy applications in water systems, nature-based solutions for urban environments, and resource recovery technologies. The research trends show increasing integration of data-driven decision support systems with environmental sustainability metrics, particularly in the water-energy-food nexus domain. Chartered Chemical Engineer (Greece) HEA Fellow (FHEA) of the Higher Education Academy Mentor in the APEX (Academic Practice & Professional Excellence Framework) scheme Member of management group of the Royal Academy of Engineering (RAE) Visiting Professors Scheme Co-leader of Circular Economy VLT in Water Europe Leader of SMART WATER Working Group in ICT4Water Cluster-EC Member of ISO standards drafting team on Circular Economy Dr Katsou has successfully supervised 16 PhD students to completion and currently supervises several ongoing doctoral projects. She has secured substantial research funding as Principal Investigator on 11 national and international projects including RESILEX Horizon Europe, SYMBIOREM Horizon Europe, BORECER Horizon Europe, HYDROUSA H2020, and WATER-MINING H2020. Her industrial consulting portfolio includes significant contracts with leading UK water industry partners such as Affinity Water, Arup, Severn Trent, and Anglian Water, with projects ranging from carbon footprint assessment to corrosion mitigation and process optimization. She leads the Transformation Tools group of the Cost Action on Circular Cities, co-leads the Circular Water VLT of Water Europe, and co-leads the SMART-WATER group of the ICT4Water Cluster-EC. Dr Katsou is also a member of the drafting team for new ISO standards on Circular Economy (Measuring and Assessing Circularity - ISO5902).

Selin AhipasaogluView profile

Professor

• Operational Research
• Convex Optimization
• Robust Optimization
• +5 more

Prof. Selin Damla Ahipasaoglu is a Professor in Operational Research at the University of Southampton's School of Mathematical Sciences . She serves on the management team of the UKRI CDT SustAI (Artificial Intelligence for Sustainability) as Senior Tutor and Co-Lead for the Transportation and Logistics Theme . Her work bridges mathematical optimization with practical applications in sustainability, finance, and transportation systems. Research Interests : Convex Optimization Robust Optimization Discrete Choice Theory Experimental Design Machine Learning Current Research : Focused on robust optimization and its applications in discrete choice modeling, portfolio optimization, and transportation systems. She explores theoretical frameworks alongside real-world implementations, particularly through interdisciplinary projects like the UKRI CDT SustAI. Teaching : In the 2025/2026 academic year, she teaches MATH3017: Mathematical Programming and MATH2013: Operational Research II . She supervises PhD students in Mathematical Sciences, including Kexin Lai, Samuel Jericho Ward, and others.

• Cultural Heritage Preservation
• Computer Science
• Architecture
• +3 more

Aleksander Gil is a Researcher at Northumbria University's Architecture and Built Environment Department, holding a Doctor of Philosophy. His work focuses on applying machine learning and data science to cultural heritage preservation, particularly in architectural documentation and building information modeling (BIM). He has contributed peer-reviewed articles to journals like Heritage and Journal on Computing and Cultural Heritage . His research interests bridge computer science and architecture, emphasizing point cloud segmentation, classification systems, and AI-driven solutions for heritage conservation. Recent studies include using random forest algorithms for UK cultural heritage buildings and critical reviews of machine learning in heritage BIM. No scientific awards or grants are explicitly mentioned in the provided text. Collaborations and network details indicate international research activity, though specific lab affiliations or student advisees are not listed.

• Signal and Information Processing
• Energy Disaggregation
• Non-Intrusive Load Monitoring (NILM)
• +15 more

Professor Vladimir Stankovic is a leading academic in the Department of Electronic and Electrical Engineering within the Faculty of Engineering at the University of Strathclyde, UK. His research focuses on signal and information processing to tackle global sustainability challenges such as energy efficiency, net-zero transition, electrification of transport, and landslide monitoring. He is actively involved in multiple high-impact research initiatives and holds leadership roles in major AI and engineering conferences. PhD (Dr-Ing), University of Leipzig, Germany, 2003 MEng (Dipl-Ing), Electrical Engineering, University of Belgrade, 2000 His research interests center on applying signal processing and AI to smart homes, micro-seismic analysis, health monitoring, remote sensing, and computer vision. He has developed innovative methods in energy disaggregation, graph signal processing, and interpretable machine learning. His work bridges engineering with sustainability, contributing to UN Sustainable Development Goals. He teaches core courses including image/video processing, communication systems, signals and systems, and information theory. The recent publications highlight a strong trend in applying AI and machine learning to energy analytics in buildings and agriculture (e.g., dairy farms), landslide monitoring using seismic data, and equitable EV charging planning. These works leverage advanced techniques such as graph neural networks, transformers, and human-in-the-loop deep learning, demonstrating a consistent focus on real-world impact, interpretability, and sustainability. He has received notable scientific awards: Finalist of the World first 10K Best paper Award (Top 3%) IEEE Multimedia Signal Processing Workshop (MMSP) top 10% best paper award 2010 Professor Stankovic has been a Principal or Co-Investigator on numerous research and knowledge exchange projects, including JED-AIs (Justice, Energy, Demand flexibility and AI for Sustainability), REMINDA, and multiple Digital Dairy Chain Innovation Vouchers. These projects are funded by EPSRC and other UKRI councils, focusing on AI-driven energy analytics, community energy sharing, and sustainable farming. He serves in key editorial roles, including Area Editor for IEEE Transactions on Communications and Associate Editor for Nature Scientific Data, and has organized major conferences such as IEEE MMSP 2017 and IJCNN 2025. He is actively involved in research teams and collaborative networks focused on AI for sustainability, energy systems, and environmental monitoring. His lab works on datasets such as the Plegma Dataset and REFIT, supporting open science in energy and seismic analytics.

Konstantinos KyriakopoulosView profile

Senior Lecturer

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +4 more

Dr. Konstantinos Kyriakopoulos is a Senior Lecturer in Cyber Intelligence, specializing in cybersecurity challenges and AI-driven solutions for converged Information and Operational Technology infrastructures. His work integrates machine learning with cyber-physical systems to enhance decision-making under uncertainty, with a focus on resilient AI algorithms and autonomous defense mechanisms. He has contributed to projects funded by Dstl, Innovate UK, and industry partners, addressing Industry 4.0 security, smart vehicles, electromagnetic attacks, and smart buildings. His research interests include adversarial machine learning, evidence theory for uncertainty modeling in ML, and autonomous cyber defense systems. He has developed novel approaches using reinforcement learning, hidden Markov models, and Bayesian optimization. His work emphasizes creating ML algorithms resistant to adversarial attacks while improving cybersecurity resilience in dynamic environments. Dr. Kyriakopoulos has also explored applications of AI in educational technology, such as automated assessment of spoken English proficiency. His recent publications focus on federated learning security, causal reinforcement learning, and anomaly detection techniques. He has experience in translating research into practical solutions, including business model pitches to investors in Canary Wharf for threat modeling tools. His contributions span over 40 peer-reviewed articles, with notable work in network intrusion detection, attack prediction via HMMs, and wavelet-based compression for network measurements. His expertise bridges academia and industry, addressing both theoretical advancements and real-world implementation challenges.

• Bioinformatics
• Health Informatics
• Affective Computing
• +4 more

Dr. Stamos Katsigiannis is an Associate Professor in the Department of Computer Science at Durham University. His research focuses on bioinformatics, health informatics, affective computing, machine learning, and GPU computing applications. He holds a PhD in Computer Science from the National and Kapodistrian University of Athens (Greece), with prior roles including Postdoctoral Research Fellow and Lecturer at the University of the West of Scotland (2016-2020). Education: BSc (Hons) Informatics and Telecommunications, National and Kapodistrian University of Athens (Greece) MSc Computer Science, Athens University of Economics and Business (Greece) PhD Computer Science, National and Kapodistrian University of Athens (Greece) Research Interests: Bioinformatics, health informatics, affective computing (e.g., emotion recognition using EEG/ECG signals), machine learning applications in medical imaging and video quality, GPU-accelerated algorithms for biomedical data analysis, and biometric identification systems. His work bridges computational methods with healthcare, education technologies, and human-computer interaction. Advising & Students: Supervising postgraduate students in AI-driven healthcare, computer vision, and affective computing. Recent collaborations include projects on AI-generated content detection (De-Factify 4.0), chest X-ray image analysis (CLN network), and trajectory prediction using graph neural networks. Labs/Teams: Active in Durham's AI research groups, contributing to interdisciplinary projects in medical imaging, cybersecurity, and educational technology. Collaborates internationally in EU-funded initiatives and UK parliamentary AI governance consultations (AGENCY project).

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +5 more

Prof Sunil Vadera is a Professor of Computer Science at the University of Salford, affiliated with the School of Science, Engineering & Environment. He holds fellowships from the British Computer Society (FBCS) and is a Chartered Engineer (CEng) and Chartered IT Professional (CITP). His leadership roles include former Dean of the School of Computing, Science and Engineering, and Director of the Informatics Research Institute. He received the UK BDO Best Indian Scientist and Engineer award in 2014 and the Amity Award for AI contributions in 2018. His research focuses on bridging theory and practice in AI, with projects like the GM AI Foundry supporting SMEs, EU-funded energy-efficient building systems, and smart meter data analysis for British Gas. His work spans AI applications in healthcare, cybersecurity, IoT, and energy systems. He leads the Deep Learning module in the MSc in AI program and has supervised multiple PhD students, including Dr Salem Ameen. Key research interests include cost-sensitive machine learning, explainable AI, phishing detection, and medical imaging. Recent publications address AI-driven solutions in healthcare (e.g., breast arterial calcification detection), cybersecurity (Arabic phishing emails), and livestock behavior analysis using vision transformers. He has pioneered algorithms like CSNL and EECSDT, advancing decision tree and Bayesian network methodologies. Prof Vadera’s contributions extend to academic leadership, including chairing the BCS Accreditations Committee. His interdisciplinary projects often involve collaborations with industry and government, emphasizing real-world impact. The Informatics Research Institute under his direction fosters innovative AI applications across sectors.

Maitreyee DeyView profile

Senior Lecturer

• Machine Learning
• Cybersecurity
• Smart Grids
• +4 more

Dr. Maitreyee Dey is a Senior Lecturer in Computer Science and Applied Computing at London Metropolitan University. She leads the GENESIS Research Lab and serves as Deputy Director in Business Engagement at the Cyber Security Research Centre. Her research focuses on machine learning applications in smart grids, healthcare technology, IoT security, and HVAC systems optimization. She has pioneered projects involving fault detection in HVAC terminal units, cybersecurity compliance for IoT devices, and non-invasive medical diagnostics using microwave technology. Her work integrates machine learning with domain-specific challenges such as voltage anomaly detection in solar farms, predictive modeling for early-stage diabetes, and grid stability analysis using micro-PMU data. She also explores educational technology innovations like the VEMeter tool for virtual classroom participation tracking and AI-driven student engagement strategies. Dr. Dey has contributed to international conferences and authored numerous papers on topics ranging from smart building automation to radiation-free medical imaging systems. Her interdisciplinary approach bridges computer science, engineering, and healthcare, with a focus on real-world impact through industry partnerships and technology commercialization.

• Wireless Communications
• Internet of Things (IoT)
• Electric Vehicles
• +6 more

Nagham Saeed serves as Associate Professor in Electrical and Electronic Engineering at the School of Computing and Engineering, University of West London, a position she has held since April 2023. Previously, she was Senior Lecturer in Electrical Engineering at the same institution from November 2017 to April 2023, following roles as Electronic Lecturer at Uxbridge College (2012-2017) and Electronic/Control Lecturer at Brunel University (2007-2012). Her academic credentials include: Ph.D. in Optimization in Wireless Networks and Communications (Brunel University, 2007-2011) M.Sc. in Mechatronics (University of Technology, Baghdad, 1997-1999) B.Eng. in Computer and Control (University of Technology, Baghdad, 1988-1992) DTLLS Diploma in Teaching (University of Westminster, 2012-2014) BAPP in Learning and Teaching (Brunel University, 2009-2010) Assessing Competence Certification (Uxbridge College, 2014) Dr. Saeed's research spans wireless communications, IoT, electric vehicles, and AI-driven energy optimization. Her work focuses on Bluetooth Low Energy applications for healthcare monitoring, battery management systems for EVs, sustainable ICT practices, and GIS-based land use analysis. She pioneers solutions for energy-efficient radio access networks and develops AI models for vehicle classification and low-resource language processing. Analysis of her 2022-2025 publications reveals three dominant trends: (1) AI integration for sustainable energy systems in telecommunications and transportation, (2) blockchain-secured vehicular networks for 6G infrastructure, and (3) cross-disciplinary applications of IoT in healthcare and environmental monitoring. Her research consistently bridges electrical engineering with computer science to solve real-world sustainability challenges. Professional recognition includes: MDPI Reviewer Acknowledgements (2020) for Algorithms, Applied Sciences, and Information journals While her 2022 educational research on feedforward teaching approaches demonstrates pedagogical engagement, no student supervision or grant management details are documented. Current institutional affiliations show no dedicated laboratory facilities or research teams specified in available records.