Find Academic Supervisors

Iain BuchanView profile

Professor

• Health Informatics
• Public Health Informatics
• Biostatistics
• +4 more

Iain Buchan is an Honorary Professor in the Division of Informatics, Imaging & Data Sciences at the University of Manchester. He directs the MRC Health eResearch Centre (HERC) and co-directs the national Farr Institute for Health Informatics Research. He also serves as Domain Director for Population Health and Ecosystems in the Faculty of Biology, Medicine and Health, and Director of Civic Analytics for the Greater Manchester Combined Authority. His research focuses on leveraging large-scale health data to accelerate scientific discovery and improve public health systems. Education includes a MD from the University of Liverpool (2000), DPH from the University of Cambridge (1999), and BSc in Pharmacology (1989). He holds advanced certifications such as FACMI (2012) and FFPH (2006). Research interests span health informatics, biostatistics, and epidemiology, with emphasis on data-driven solutions for public health challenges. His work includes developing methodologies like 'Research Objects' and 'e-Labs' to enhance health data analytics, and initiatives like the Connected Health Cities program. He has secured £100M+ in research grants and leads one of the UK’s top health informatics teams. Key achievements include founding the Centre for Health Informatics, advancing clinical audit systems, and pioneering health system-wide data integration. Awards include Fellowships in Medical Informatics and Public Health. His projects address topics such as drug safety, chronic disease management, and civic health analytics. Teaching focuses on health informatics leadership through doctoral training and professional development programs. He collaborates internationally via WHO, IMIA, and other networks to promote global health data sharing.

• Traditional Chinese Medicine (TCM)
• Data Mining
• Medical Informatics
• +4 more

Associate Professor Josiah Poon is affiliated with the School of Computer Science at the University of Sydney. His research focuses on applying data mining and IT techniques to Traditional Chinese Medicine (TCM), particularly analyzing herbal combinations for effective treatments. He collaborates with institutions in China to improve TCM evidence and has contributed to clinical data analysis, medical informatics, and multimodal AI systems. Teaching includes courses such as INFO1003 (Foundations of IT) and INFO9003 (IT for Health Professionals). Current research students are Rina CABRAL (Multimodality Representation), Yan LI (Long Document Comprehension), and Xiaobin LU (Financial Decisions). Research highlights include developing algorithms to quantify TCM efficacy, analyzing complementarity in herbal combinations, and applying machine learning to healthcare data. Notable projects include a randomized controlled trial on pneumococcal vaccination (2021) and a Google-funded multimodal health detection system (2020). Key areas of expertise span TCM informatics, medical data analytics, and AI-driven healthcare solutions. His work bridges Eastern/Western medicine through computational methods, emphasizing evidence-based practices in TCM.

• Healthcare Informatics
• Artificial Intelligence
• Machine Learning
• +3 more

Maqbool Hussain is a Senior Lecturer in Computer Science at the College of Science and Engineering. His research focuses on healthcare informatics, artificial intelligence (AI) applications in medical decision-making, and the development of knowledge-based systems for aerospace and healthcare sectors. He has contributed significantly to areas such as digital twin frameworks for critical care workflows, clinical decision support systems, and semantic interoperability in healthcare. Research Interests Hussain’s work spans multiple disciplines, including: Healthcare Informatics and AI-driven medical solutions Knowledge Graphs and Large Language Models (LLMs) in healthcare and aerospace Digital twins for optimizing critical care and aerospace maintenance Data-driven clinical decision support systems Medical data security and interoperability standards Machine learning for text annotation and classification Recent Research Trends Recent publications highlight his focus on integrating advanced technologies like LLMs and digital twins into healthcare and aerospace contexts. His work addresses challenges in critical care workflow optimization, kidney disease diagnosis, and aerospace product maintenance through innovative knowledge graph approaches. He also explores the application of transformer-based models for text analysis and the secure exchange of medical data using biometric methods. Labs and Teams Hussain is affiliated with the College of Science and Engineering, contributing to interdisciplinary research teams focused on healthcare technology, aerospace systems, and AI applications. His collaborations span academic and industry partners, emphasizing practical solutions for healthcare informatics and aerospace engineering challenges.

Xuebin WeiView profile

Associate Professor

• Geographic Information Systems (GIS)
• Social Media Analysis
• Machine Learning
• +4 more

Xuebin Wei is an Associate Professor of Geography at the College of Integrated Science & Engineering (CISE) at James Madison University (JMU). He holds a Ph.D. in Geography from the University of Georgia, complemented by advanced degrees in GIS and Urban Planning from Wuhan University and ITC at the University of Twente. Dr. Wei specializes in integrating geospatial technologies with social media analysis, machine learning, and cloud computing to address urban and environmental challenges. His research focuses on spatial-social networks, 3D urban modeling using LiDAR and aerial imagery, and applying social media data for disaster response and public health. Notable projects include the JMU Virtual 3D Campus and LBSocial initiative exploring geosocial data frameworks. Wei teaches courses in GIS, cloud computing (AWS), programming for data science, and machine learning. His publications span topics like election prediction using Twitter data, spatial analysis of climate phenomena (El Niño), and optimizing urban transit infrastructure. While no specific awards are listed, his work reflects interdisciplinary innovation at the intersection of geography, technology, and society. He advises students in CISE's data science and geospatial programs through courses like IA340 Data Mining and GEOG215 Cartography.

William MarcellinoView profile

Professor

• Artificial Intelligence
• National Security
• Social Media Analysis
• +5 more

William Marcellino is a Senior Behavioral and Social Scientist at the RAND Corporation and a Professor of Text Analytics at the RAND School of Public Policy. He also serves as a lecturer at Carnegie Mellon University, where he earned his Ph.D. in rhetoric. His academic and research roles focus on AI applications, such as developing RAND-Lex, a proprietary text analytics tool, and teaching NLP and qualitative methods. Marcellino’s research expertise spans information operations, national security, social media analysis, and military technology. He previously served as a U.S. Marine tank officer and enlisted rifleman, informing his work on military resilience and defense-related AI acquisition. His recent work addresses AI’s role in disinformation, China’s AI exports, and ethical frameworks for influence operations. Education: Ph.D. in Rhetoric, Carnegie Mellon University Key Projects: RAND-Lex development, China AI Export Database, command narrative frameworks Notable Contributions: Analysis of social media’s role in conflict (e.g., Israel-Hamas, Ukraine-Russia), counter-radicalization strategies, and AI ethics.

Richard N. LandersView profile

Professor

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

Richard N. Landers is the John P. Campbell Distinguished Professor of Industrial-Organizational Psychology at the University of Minnesota, where he leads the TNTLAB (Testing New Technologies in Learning, Assessment and Behavior). His research focuses on applying innovative technologies—including artificial intelligence, gamification, and virtual reality—to enhance psychometric assessment, employee selection, adult learning, and research methodology in organizational contexts. He serves as associate editor for the International Journal of Selection and Assessment and holds editorial roles in several other journals. Research Interests : Integration of AI in workplace assessment, gamification of training systems, virtual reality applications, and psychometric validation of technology-driven methods Key Contributions : Development of the Work-Related Social Media Questionnaire (WSMQ) and the Cambridge Handbook of Technology and Employee Behavior His work has been published in American Psychologist , Journal of Applied Psychology , and Psychological Methods , with interdisciplinary impact in Computers in Human Behavior . He maintains industry connections through Landers Workforce Science LLC and Aon's scientific advisory board, while also creating educational tools like the Web Scraping of Psychological Data tutorial and Online Automated Statistics Tutor . Scientific Recognition : Fellow of three major psychological societies Training : Mentors Ph.D. and undergraduate students in I-O psychology and technology applications

Ella HaigView profile

Associate Professor

• Intelligent Systems
• User Modelling and Personalisation
• Data Mining
• +7 more

Ella Haig is an Associate Professor of Artificial Intelligence at the University of Portsmouth, UK, affiliated with the School of Computing within the Faculty of Technology. She is also a member of the Portsmouth AI and Data Science Centre, Future of Law, Innovation and Technology Research Centre, and Centre for Cybercrime and Economic Crime. Her academic journey includes a PhD in Computer Science from Birkbeck College (University of London), an MSc in Learning Technologies from the National College of Ireland, and a Postgraduate Certificate in Learning and Teaching from the University of Portsmouth. Her research focuses on Intelligent Systems, User Modelling, Data Mining, and Decision Support, with notable contributions to emotion recognition, machine learning, and educational data mining. Ella has published over 140 works, including articles on multimodal emotion detection and comparative analyses of AI models like GPT-3 and BERT. She actively contributes to conferences, such as the IEEE World Congress on Computational Intelligence and the International Conference on Educational Data Mining. Ella has secured grants totaling over £235,000 for projects like the KTP Citizens Advice initiative, exploring technology solutions for public services. Her work aligns with UN Sustainable Development Goals, particularly in advancing education and innovation. Notable achievements include a 2023 Best Paper Award for her research on multimodal emotion recognition systems.

• Pervasive Computing
• Wireless Sensor Networks
• Healthcare Informatics
• +3 more

John Herbert is a Senior Lecturer in Computer Science at University College Cork (UCC), Ireland. His research focuses on pervasive computing, wireless sensor networks, and healthcare informatics, with notable projects like the CARA framework for falls assessment in the elderly. He holds a PhD in Computer Science from Cambridge University and has held visiting roles at institutions including SRI International and the University of Cambridge. Education: BSc (Experimental Physics), MSc (Experimental Physics), Postgraduate Diploma (Computer Science) from UCC; PhD (Computer Science) from Cambridge University. Research Grants: Led projects funded by Science Foundation Ireland (€163,726) and the Irish Research Council (€71,250), focusing on cloud computing and healthcare applications. His work emphasizes context-aware systems, data quality in medical environments, and real-time analysis. Selected awards include an International Fellowship from Digital Systems Research Center (1989) and visiting fellowships at Cambridge (2008-2009). Teaching: Courses include Advanced Software Engineering, Formal Methods, and Model-Based Software Development. Outreach: Advisor to award-winning student teams (e.g., IEEE mobile app contest) and collaborator with industry partners in China and Europe.

Shuo YuView profile

Assistant Professor

• Health Analytics
• Interpretable Deep Learning
• Text Mining
• +4 more

Shuo Yu is an Assistant Professor of Information Systems and Quantitative Sciences at the Rawls College of Business, Texas Tech University, and serves as the Wetherbe Professor in Management Information Systems. He directs the MIS Doctoral Program and teaches courses such as Big Data Security, Information Security, and Data Analytics Tools. Yu holds a PhD from the University of Arizona (Management Information Systems) and a BBA from Tsinghua University (Information Management). His research focuses on data science applications in healthcare analytics, cybersecurity, and e-commerce. Key areas include interpretable deep learning, text mining, and mobile health technologies. Notable projects include SilverLink, a smart home monitoring system for senior care using wearable sensors and machine learning. Yu’s publications span journals like MIS Quarterly and IEEE Transactions, emphasizing innovations in health profiling, fall prevention, and recommendation systems. His work integrates techniques such as Hidden Markov Models, Generative Adversarial Networks, and Bayesian networks. No scientific awards are listed. He is actively involved in advising doctoral students and contributes to the Association for Information Systems (AIS).

• Tool-based Text Analysis
• Artificial Intelligence in Literary Analysis
• Poetics of Travel Writing
• +6 more

Veronique MAGRI is a Professor of Exceptional University Class at Université Côte d'Azur (UCA), affiliated with the Department of Modern Literature. She leads research in textual analysis and digital humanities, focusing on computational methods in literary studies. Her roles include directing the Logométrie research team (2014–2018) and the Nouvelles textualités axis (2018–2022) within the CNRS UMR 7320 Bases, Corpus, Language (BCL). She serves on ANR’s Scientific Evaluation Committee (CE 38), HCÉRES, and UCA’s academic governance bodies. Her administrative roles include leading the Department of Modern Literature (2009–2013) and overseeing the Saint-Raphaël Connected Campus (2020–present). Education: 2006: Habilitation to Direct Research (Université Côte d'Azur) 1993: Doctorate in Language Sciences and Techniques (university unspecified) 1989: External Aggregation of Modern Letters Research focuses on AI-driven textual analysis, travel narrative poetics, and stylistics. She pioneers digital humanities tools for corpus-based studies and explores linguistic patterns in modern French literature. Recent work includes applying deep learning to authorship analysis and examining migrant narratives through textual linguistics. Advising and grants: She co-created the distance-learning Master of Letters program and has held leadership in institutional committees. Her grants include ANR-funded projects and collaborations with international agencies like FNRS. Labs/Teams: Director of BCL’s Logométrie team and Nouvelles textualités research axis, advancing interdisciplinary textual studies.

Ahmed Abdeen HamedView profile

Assistant Professor

• Drug Repurposing
• Network Analysis
• Artificial Intelligence in Healthcare
• +6 more

Dr. Ahmed Abdeen Hamed is a former Assistant Professor of Data Science and Artificial Intelligence at Norwich University and a former Research Team Leader in Clinical Data Science. He holds a Ph.D. from the University of Vermont (2014) and has extensive industry experience in pharmaceutical research. His work focuses on computational methods for drug discovery, network analysis, and AI-driven healthcare solutions, particularly in drug repurposing for diseases like COVID-19. He has developed algorithms such as MolecRank and NeoNet, and holds a patent for specificity-based molecule ranking systems. Education: PhD in Data Science (University of Vermont, 2014). Research Interests: Network-based drug discovery, biomedical informatics, AI in healthcare, clinical data science, and combating misinformation using machine learning. His recent work emphasizes leveraging clinical trials and biomedical literature to predict treatment efficacies through computational frameworks. Key Contributions: First inventor on a molecule ranking patent (2021), co-developer of the CovidX algorithm for drug repurposing, and supervisor of PhD students/postdoctoral fellows. Collaborates with Sano teams to advance clinical research through AI. Awards: FastCompany Most Creative (2016) Industry Impact: Contributed to a multi-million dollar grant for a recommendation engine startup. Labs/Teams: Currently part of Sano's research teams, focusing on computational clinical research and interdisciplinary collaborations.

• Machine Learning
• Toxicology
• Computational Biology
• +4 more

Keerthana Jaganathan is a researcher at Northumbria University, specializing in the application of machine learning to toxicology and health risk assessment. Her work bridges computational biology, artificial intelligence, and chemical safety analysis. Her research focuses on developing explainable AI models for toxicity prediction, including applications in respiratory, liver, and mitochondrial toxicity. She has published extensively on multimodal fusion approaches, feature selection techniques, and hybrid molecular representations in predictive toxicology. Recent publications highlight her expertise in deep learning for dermal toxicity assessment, fuzzy mutual information for multi-label classification, and comparative studies of tree-based ensemble models in pulmonary toxicity prediction. While specific departmental affiliations are not detailed in the provided texts, her work aligns with interdisciplinary research initiatives at Northumbria.

• Edge Computing
• Fog Computing
• Cloud Computing
• +4 more

Dragi Kimovski is a Habilitated Assistant Professor in Distributed Systems at Klagenfurt University, Austria, focusing on Edge Computing and AI. He previously held roles at the University of Innsbruck and the University of Information Science and Technology in Macedonia. His research spans Edge/Fog/Cloud computing, multi-objective optimization, and high-performance computing. He has coordinated major projects like 6GContinuum and KärtnerFog, and led initiatives such as DataCloud and ASPIDE. His teaching includes courses on Distributed Computing, Cloud Computing, and IoT. He is the co-creator of the Carinthian Computing Continuum and maintains a blog on Edge AI World. His work emphasizes sustainable and efficient computing solutions for emerging technologies. Education: Not explicitly listed in the provided text. Research Interests: Edge Computing, Fog Computing, Cloud Computing, Multi-objective Optimization, High-Performance Computing, AI in Distributed Systems. His work addresses challenges in resource management, latency reduction, and scalability across heterogeneous environments, with applications in healthcare, IoT, and 6G networks. Projects: 6GContinuum (Coordinator): Focuses on AI services over 6G networks. KärtnerFog (Scientific Coordinator): Develops adaptive Fog infrastructures over 5G. DataCloud (WP5 Leader): Manages Big Data pipelines on the Computing Continuum. ASPIDE (Scientific Coordinator): Advances exascale programming models for data processing. Teaching: Klagenfurt University: Courses include Distributed Computing, IoT, Cloud Computing, and Advanced Programming. University of Innsbruck: Taught Advanced Parallel and Distributed Systems. University of Information Science and Technology: Courses in High-Performance Computing and Network Architectures. Labs/Teams: Co-created the Carinthian Computing Continuum, an automated SDN testbed for Edge computing research. Active in interdisciplinary teams addressing extreme data processing and sustainable computing.

Muhammed-Fatih KayaView profile

Researcher

• Natural Language Processing
• Machine Learning
• Pattern Recognition
• +3 more

Muhammed-Fatih Kaya is a postdoctoral researcher and research coordinator at the Chair of Information Systems and Intelligent Systems within the Faculty of Economics and Social Sciences at the University of Hohenheim. He also heads the Business Information Systems Service Center, which manages program administration and academic advising for Business Information Systems programs at the Universities of Hohenheim and Stuttgart. Dr. Kaya earned his Master of Science in Business Informatics from the Universities of Hohenheim and Stuttgart and completed his doctorate in machine learning in August 2022 with the grade 'summa cum laude' (very good with distinction). His dissertation focused on 'Automated Pattern Recognition of Communication Behavior in Electronic Business Negotiations.' His research spans multiple domains at the intersection of artificial intelligence and business processes, with primary interests in natural language processing, machine learning, pattern recognition, predictive analytics, electronic negotiations, and negotiation support systems. Dr. Kaya's work consistently applies AI techniques to understand and improve business communication and negotiation processes, demonstrating a strong trajectory from foundational pattern recognition research to current applications of deep learning in digital negotiations. Dr. Kaya's scholarly contributions reveal an evolving research focus that has progressed from analyzing communication patterns in negotiations to exploring cutting-edge AI applications in business contexts, with increasing emphasis on practical implementations of machine learning in business processes and educational frameworks for AI competencies. Springer Group Decision and Negotiation Young Researcher Award (2019) Springer Best Paper Award at the International Group Decision and Negotiation Conference in Tokyo (2023) Dr. Kaya serves actively in academic service roles, including as a member of the editorial board of the Group Decision and Negotiation Journal since 2023 and as a reviewer for various business information systems publications. He participates in the ABBA: AI for Business | Business for AI project coordinated by the University of Hohenheim. His committee work includes membership on the Master's program admissions committee (since 2019), Bachelor and Master Study Committees (since 2020), the Senate Commission for Studies and Teaching (since 2020), and the Faculty Council of the Faculty of Economics and Social Sciences (since 2022). As head of the Business Information Systems Service Center, Dr. Kaya oversees program management and academic advising for the joint Bachelor's and Master's programs in Business Information Systems at the Universities of Hohenheim and Stuttgart, demonstrating his commitment to both research excellence and educational leadership.

• Neuroengineering
• Rehabilitation Engineering
• Biomedical Engineering
• +3 more

Baldassarre D'Elia is a Researcher affiliated with the Department of Bioengineering at University of Roma Tre, associated with BioLab³. He holds a MSc in Electrical Engineering (1992) and PhD from Sapienza University of Rome (1996), followed by postdoctoral research there (2000). Since 2010, he has been involved in the Bioengineering Doctoral School at Roma Tre. His research focuses on neuroengineering applications in rehabilitation, particularly using haptic systems to aid post-stroke and Parkinson's patients. He explores movement regularity metrics in elderly populations through haptic feedback analysis. Education: MSc (Electrical Engineering, Sapienza 1992), PhD (Sapienza 1996), Postdoc (Sapienza 2000), current involvement in Roma Tre's Bioengineering Doctoral School. Research emphasizes haptic platforms for motor learning, quantifying movement parameters using kinematic data. His work bridges clinical needs with engineering solutions, addressing both neurological disorders and geriatric rehabilitation challenges. Publications (2012–2016) highlight studies on haptic feedback efficacy, comparison of visual/haptic modalities, and development of analytical frameworks for rehabilitation metrics. No awards explicitly mentioned but active in international conferences (ECCE, ICNR, Mediterranean Conferences). Associated with BioLab³, focusing on interdisciplinary projects combining neuroengineering and clinical applications. No formal advising role documented in provided texts.