Andreas Vlachos is a Professor of Natural Language Processing and Machine Learning at the Department of Computer Science and Technology, University of Cambridge, and holds the Dinesh Dhamija Fellowship at Fitzwilliam College. His research spans dialogue modeling, automated fact-checking, imitation learning, semantic parsing, biomedical text mining, and trustworthiness in AI systems. PhD in Computer Science, University of Cambridge (supervised by Ted Briscoe and Zoubin Ghahramani) Lecturer at University of Sheffield Postdoctoral roles at UCL, University of Cambridge (NLIP group, Stephen Clark), and University of Wisconsin-Madison (Mark Craven) Current research focuses on evaluating and mitigating biases in language models, advancing fact-checking methodologies, and improving model robustness through interpolation, reinforcement learning, and causal reasoning. His work integrates natural logic, knowledge graphs, and multimodal evidence for verification tasks. Recent publications address uncertainty quantification, temporal planning benchmarks, and ethical framing of NLP artifacts. Grants from ERC, EPSRC, Facebook, Google, and the Alan Turing Institute fund his research team. Collaborations include Sebastian Riedel, Stephen Clark, and Mark Craven. Key projects explore disinformation detection, long-form generation, and confidence calibration in AI systems.
Dr Jacopo de Berardinis is a Lecturer (Assistant Professor) in Music AI, focusing on computational methods for music analysis and information retrieval. His work spans three key areas: Computational Creativity , Music Intelligence and Personalisation , and the Semantic Music Web , aiming to enhance musical understanding and education through AI-driven agents. Prior to his current role, he held positions at the University of Manchester (S+T+ARTS MUSAE project) and King's College London (EU H2020 Polifonia project, where he led the INTERLINK pilot). He earned a PhD in Machine Learning from the University of Manchester, specializing in the automatic evaluation of generative models for music composition. Scientific awards include the AHRC Innovation Accelerator Grant (2022-2026), supporting interdisciplinary research at the intersection of artificial intelligence and musicology. His work emphasizes personalized music experiences for well-being and advancing creative applications of AI in music.
Vaishak Belle is a Reader in Logic and Learning at the School of Informatics, University of Edinburgh, and serves as Director of Research and Innovation at the Bayes Centre (40% position). His academic career focuses on the critical intersection of artificial intelligence, formal logic, and machine learning systems. His research spans multiple domains within AI: Neurosymbolic AI integration approaches Logic-based machine learning frameworks Ethics, fairness, and responsibility in AI systems Generative AI and its societal impact Robotics with advanced reasoning capabilities Causal modeling and probabilistic reasoning Belle leads a research laboratory dedicated to advancing neurosymbolic AI, which combines the explainability of symbolic systems with the learning capabilities of neural networks. His recent work has explored abduction in logical frameworks, formal languages for AI safety, and the relevance of logic for general-purpose AI systems. He has made significant contributions to bridging the gap between theoretical AI foundations and practical applications. His publications demonstrate consistent focus on creating AI systems that can reason formally while learning from data, with applications ranging from robotics to ethical decision-making frameworks. His research addresses fundamental challenges in developing trustworthy, explainable AI that can operate safely in complex environments. Beyond technical research, Belle is actively engaged in AI education through executive programs on AI leadership and ethics, and has contributed to public understanding through his children's book "The girl and the robot" which explores human-robot relationships and emotional projection onto artificial agents. He maintains an active presence in the international AI research community, regularly participating in major workshops including Dagstuhl seminars on neurosymbolic AI, and collaborating with researchers across disciplines from computer science to philosophy.
Michael Goldsmith is a Senior Research Fellow at the Department of Computer Science and Worcester College, University of Oxford. He holds multiple leadership positions including Director of the Oxford Martin Programme on AI Threat Detection, Associate Director of the Cyber Security Centre, and Co-Director of the Centre for Doctoral Training in Cybersecurity. His research bridges formal methods, concurrency theory, and practical cybersecurity applications. Goldsmith's research focuses on cybersecurity analytics including threat detection, risk management, and trust frameworks. He pioneered automated cryptoprotocol analysis and investigates multidisciplinary projects spanning mathematical models to socio-technical systems. His core interests include formal verification, AI threat landscapes, privacy architectures, and security protocol design. Analysis of his recent publications reveals strong emphasis on practical cybersecurity challenges: 63% focus on threat detection (especially insider threats), 22% on trust/risk frameworks, and 15% on formal methods applications. His work consistently integrates technical security mechanisms with human factors and organizational contexts. He currently advises Ahmed Salman and has supervised 10+ students including Mary Bispham, Rodrigo Carvalho, and Elizabeth Phillips. His research teams collaborate on projects funded by Technology Strategy Board, government agencies, and industry partners. Goldsmith leads the Oxford Martin Programme on AI Threat Detection and co-directs the Centre for Doctoral Training in Cybersecurity. His research group develops tools for security visualization (CyberVis), trust metrics, and identity management frameworks.
Professor Sir Nigel Shadbolt is Principal of Jesus College Oxford and Professor of Computing Science at the University of Oxford. He is Chairman and Co-founder of the Open Data Institute which he established with Sir Tim Berners-Lee. His career spans multiple prestigious institutions including the University of Southampton and University of Nottingham, where he held leadership roles in AI research. He has served in significant government advisory positions including as Information Advisor to the UK Prime Minister and member of the Public Sector Transparency Board. Nigel Shadbolt earned his undergraduate degree in Philosophy and Psychology from the University of Newcastle (1st Class Honours, 1978) followed by a PhD in Artificial Intelligence from the University of Edinburgh. His academic journey includes positions as the Allan Standen Professor of Intelligent Systems at Nottingham and leadership of the Web and Internet Science Group at Southampton before joining Oxford. Shadbolt's research spans the interdisciplinary field of Web Science, which he helped originate, focusing on human-centered AI, social machines, open data, and ethical considerations in technology. His work examines how humans and computers integrate at web scale to create novel applications, with recent emphasis on children's digital autonomy and privacy. He has published over 500 articles exploring topics from cognitive psychology to computational neuroscience, Artificial Intelligence to the Semantic Web. His notable contributions include the development of data.gov.uk and leadership in establishing Oxford's Institute of Ethics in AI. His 2018 book 'The Digital Ape: how to live (in peace) with smart machines' has been described as a 'landmark book' in the field. Knighted in 2013 for services to science and engineering Fellow of The Royal Society (FRS) Fellow of the Royal Academy of Engineering (FREng) Fellow of the British Computer Society (FBCS) Technology Pioneer status by the Davos World Economic Forum UK national BT Flagship IT Award As an advisor, Shadbolt has supervised numerous PhD students who have gone on to positions at Google DeepMind, the World Bank, and other prestigious institutions. His research has been supported by multiple grants including SOCIAM, KOALA, and ReTiPS projects. He co-founded Garlik Ltd, which was acquired by Experian, demonstrating his commitment to translating research into practical applications that benefit society. Shadbolt leads the Web and Internet Science research group at Oxford, focusing on social machines - applications that succeed at web scale by integrating humans and computers in novel ways. His work on the KOALA Hero Toolkit and CHAITok system addresses critical challenges in children's data autonomy on social media platforms, reflecting his commitment to ethical technology design.
David De Roure is Professor of e-Research at the University of Oxford and Academic Director of both the Digital Scholarship initiative and the Laboratory for AI Security Research. He is also an Honorary Research Professor at the Royal Northern College of Music (RNCM), where he serves as Technical Director of the Centre for Practice & Research in Science & Music (PRiSM). His work bridges computer science, digital humanities, cybersecurity, and music through his distinctive interdisciplinary approach. De Roure received his PhD in 1990 supervised by David W Barron and Peter Henderson, with research in Lisp and distributed systems. Prior to joining Oxford in 2010, he was Professor of Computer Science at the University of Southampton and Director of the Centre for Pervasive Computing in the Environment. His career spans multiple institutions and research domains, reflecting his commitment to interdisciplinary work. De Roure's research focuses on new methods of digital scholarship, innovation in knowledge infrastructure, cybersecurity, and computational approaches to music. His work uniquely combines humanities (digital musicology), social sciences (social machines and web science), engineering (Internet of Things), and computer science (distributed systems, AI). A key theme is empowering human creativity through technology rather than replacing humans with AI. He emphasizes co-creation between humans and machines, particularly in music composition where he explores how algorithms can generate fragments for human assembly. His recent publications reveal a strong focus on AI security in IoT systems, digital scholarship methods, and the intersection of music with computational approaches. There's a clear trajectory from foundational work in social machines and web science toward current applications in cybersecurity and music-AI co-creation. His publications consistently bridge technical domains with humanistic inquiry, demonstrating his commitment to interdisciplinary scholarship that addresses real-world challenges. Fellow of the British Computer Society (FBCS) Fellow of the Institute of Mathematics and its Applications (FIMA) Fellow of the Royal Society of Arts (FRSA) Chartered IT Professional (CITP) Turing Fellow at The Alan Turing Institute (2018-2024) De Roure has co-founded three major interdisciplinary initiatives: PETRAS National Centre of Excellence for IoT Systems Cybersecurity (the world's largest socio-technical research center focused on IoT security), the Software Sustainability Institute (dedicated to improving research software), and PRiSM at RNCM. He was Director of the Oxford e-Research Centre from 2012-17 and has led numerous research projects including SOCIAM (The Theory and Practice of Social Machines), FAST (Fusing Audio and Semantic Technologies), and Transforming Musicology. The Laboratory for AI Security Research, which he directs, took its first PhD students in 2024. At Oxford, De Roure chairs the Digital Research Cluster at Wolfson College and oversees the Laboratory for AI Security Research. The PRiSM team at RNCM has produced numerous musical works and performances, including six premieres in New York in 2024. He has been involved in designing gesture recognition software used in many performances and has collaborated on public engagement projects including the Science Together project which released a Hip Hop album. His current work includes exploring Chladni Plates for new musical instrument design and developing algorithmically enhanced instruments.
Jiaoyan Chen is a Lecturer (Assistant Professor) in the Department of Computer Science at The University of Manchester, set to become a Senior Lecturer (Associate Professor) from July 2025. Previously, she served as a Senior Researcher at the University of Oxford and held postdoctoral roles at Heidelberg University. Her research focuses on neural-symbolic knowledge representation, ontology engineering, and integrating large language models with knowledge graphs. Education: PhD in Knowledge Reasoning and Predictive Analytics (Zhejiang University, 2011-2016) and BEng in Computer Science (Zhejiang University, 2007-2011). She also spent time as a visiting scholar at Zurich University (2014-2015). Research Interests include: Knowledge Graphs, Ontologies, Large Language Models, Retrieval Augmented Generation, and Machine Learning applications in knowledge-aware systems. She leads major grants such as the EPSRC New Investigator Award (EP/Y017706/1) and collaborates internationally through initiatives like the Manchester-Melbourne-Toronto Fund. Teaching: Leads units like 'Data Engineering Technologies' and 'Advanced Topics in Knowledge Representation'. She actively advises PhD students and co-develops tools like OWL2Vec* and DeepOnto. Service roles include Associate Editor of Transactions on Graph Data and Knowledge (TGDK), membership in the EPSRC Peer Review College, and leadership in ontology alignment initiatives like OAEI Bio-ML Track.
Professor Leif Isaksen is a leading scholar in Digital Humanities and Ancient History at the University of Exeter, holding a chair in the Department of Classics, Ancient History, Religion and Theology. He also serves as Theme Lead for Humanities, Heritage and the Creative Industries at the Institute for Data Science and Artificial Intelligence (IDSAI). With a background in archaeology and a focus on Spatial-temporal representation in humanities Intelligent systems for historical data Digital skills development in arts and humanities , his work bridges classical scholarship and computational innovation. His research includes Pelagios Network projects like Recogito and Peripleo , which revolutionized semantic annotation and geospatial analysis of ancient texts. He directed the Cluny Hill Dig and co-founded initiatives like Hot Source! and DISKAH to democratize digital humanities skills. Key professional roles include: Executive Board Chair of ADHO (2019-2021) Co-Director of Web Science CDT at Southampton Active leadership in CAA, EADH, and ISHMap Scientific honors include fellowships at the Society of Antiquaries of Scotland and former affiliations with the Alan Turing Institute and Society of Antiquaries of London . His work aligns with UN Sustainable Development Goals 9: Industry, Innovation and Infrastructure and 4: Quality Education .
Dr Kun Wei is a Lecturer in Computer Science at the University of the West of England (UWE), joining in 2015. Previously, he worked as a Research Associate at the University of York, focusing on timing properties of complex systems and formal development of safety-critical applications. His research spans formal verification, security protocols, concurrent programming, and model-checking tools. BSc in Computer Science MSc in Internet Computing PhD in Computer Science from the University of Surrey His expertise includes the analysis of timing properties in social-technical systems and cyber-physical systems using the timebands model, as well as formal verification of security protocols. He specializes in object-oriented software development , concurrent programming , and semantics of programming languages , with applications in safety-critical and dependable systems . His work integrates theorem-proving and model-checking tools for system development and verification.
Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.
Dr Matthew Shardlow is a Reader in the Department of Computing and Mathematics at Manchester Metropolitan University . His career spans teaching and research, with a focus on Natural Language Processing (NLP) and its applications in Text Mining across disciplines like Neuroscience , Chemistry , Finance , and Journalism . He leads the Natural Language Processing Lab , which explores the use of Large Language Models (LLMs) in text-based applications. Key research areas include: Text Simplification : Developing methods to make complex texts accessible. Emoji Analysis : Understanding emoji usage in language and machine interpretation. Text Mining : Applying NLP to diverse fields like healthcare and education. Matthew’s recent publications highlight advancements in LLMs , lexical simplification , biomedical text processing , and AI ethics . He actively mentors BSc , Master’s , and PhD students aligned with his interests and maintains collaborations through the OpenMinTeD project and National Centre for Text Mining . Contact: m.shardlow@mmu.ac.uk .
Stuart E. Middleton is a Professor in the Electronics and Computer Science (ECS) department at the University of Southampton, where he has been employed since 2003. His research bridges artificial intelligence with practical applications in social science, mental health, and security domains. He leads multiple research projects funded by DTP and CISDnS CDT, focusing on multimodal natural language processing and large language models for social good applications. Professor Middleton's research interests center on Natural Language Processing, Large Language Models, and Human-in-the-loop AI systems. His work spans mental health applications (particularly suicide risk detection and mood change analysis), social media analysis for crisis mapping, geoparsing for location extraction, and argument mining in political discourse. He has developed numerous open-source NLP projects and datasets including CPIQA for climate science, ConversationMoC for mental health monitoring, and M-Arg for multimodal argument mining. His research demonstrates how AI can effectively support human decision-making in critical domains like mental healthcare, defense applications, and crisis management. His recent publications reveal a strong trend toward applying LLMs to high-impact societal challenges, particularly in mental health monitoring and climate science verification. He has pioneered methods for detecting suicidal ideation in social media, identifying moments of mood change, and developing context-aware question answering for climate papers. His work consistently emphasizes the importance of human oversight in AI systems, with numerous publications on responsible AI, regulation, and human-in-the-loop approaches. Ranked 1st in ECAL-2024 shared task on suicidal ideation detection Ranked 1st in NAACL-2022 shared task on suicide risk and mood change classification Winner of 'best paper' award at WWW2002 Semantic Web Workshop Professor Middleton actively supervises PhD students through multiple funded projects including 'Multimodal Natural Language Processing for Computational Social Science', 'Large Language Models for Military Veteran Mental Health', and 'Large Language Models for Human/AI Information Foraging to Combat Digital Human Trafficking into Terrorism'. He has secured significant funding from UKRI, DSTL, and other sources to support his research in responsible AI applications. He organizes major workshops including the RAI UK Workshops on Responsible AI for Mental Health and AIUK workshops on AI for Data Rescue and Defense applications. His research group maintains numerous GitHub repositories with open-source NLP tools and datasets that have been widely adopted by the research community.
Ali Hamie is a Senior Lecturer at the School of Architecture, Technology and Engineering (University of Brighton, UK), specializing in formal methods in software engineering and ontology modeling. With over 35 publications, his work bridges theoretical formalisms like UML, OCL, and JML with practical implementation validation. BSc in Pure Mathematics (Lebanese University, 1982) Postgraduate Diploma in Computing (University of Essex, 1986) MSc in Computer Science (University of Essex, 1987) PhD in Computer Science (University of Essex, 1991) His research focuses on formal aspects of software development , including specification patterns, design by contract, and translation between formal notations (OCL to JML). Recent work examines diagrammatic reasoning in ontology engineering and hybrid modeling approaches combining formal and agile methods. Studies show his publications span formal methods , ontology modeling , and constraints validation , with recurring themes in OCL-JML interoperability, diagrammatic notations, and user-centric formalism evaluation. Awards include Fellow of the Higher Education Academy (2017) . He supervises research in formal computing, with past topics covering concept diagrams and ontology modeling. His academic career includes postdoctoral roles at Newcastle University and EPSRC-funded work at Imperial College.
Dr. Andrew Hardie is a Reader in Linguistics at Lancaster University, holding a position equivalent to Associate Professor. He is affiliated with the Faculty of Humanities, Arts and Social Sciences and the Department of Linguistics and English Language within the School of Social Sciences. His primary research specialism focuses on corpus-based methodology and its applications across various disciplines: Corpus design and construction methodologies Development of corpus analysis software tools Applications in grammar of English and other languages Extensions to discourse analysis, language teaching, and other humanities and social sciences fields Dr. Hardie's work spans both theoretical and applied linguistics, with particular emphasis on adapting corpus methods for social scientists and humanists in fields including Psychology, Geography, History, and English Literature. His expertise extends to multiple languages, with special focus on South Asian languages such as Nepali, Urdu, and Hindi. He has developed several significant software tools for corpus linguistics, including Corpus Workbench (as a lead developer), CQPweb (as creator), Unicodify, and Unitag, which have substantially advanced the field of corpus linguistics methodology. His research portfolio includes major projects like the ESRC Centre for Corpus Approaches to Social Science (where he serves as Deputy Director) and UCREL (where he is Chair), demonstrating his leadership in the field. His work bridges theoretical linguistics, computational methods, and practical applications across multiple disciplines. Dr. Hardie actively supervises PhD students working on diverse topics from collocational errors in language learning to sociolinguistics of swearing in Arabic, reflecting the breadth of his research interests and influence across linguistic subfields.
Professor Xiaodong Liu is a faculty member at Edinburgh Napier University, affiliated with the School of Computing, Engineering and the Built Environment . His research spans Internet of Things , Edge Computing , Artificial Intelligence , and Cybersecurity , with a focus on decentralized systems and data-driven decision-making. Research Themes : IoT orchestration, federated learning, smart city infrastructure, building maintenance optimization, and automotive cybersecurity. Current Projects : Leading Swarmchestrate (EU-funded), Long-range Perceptive Autonomous Vehicles (Royal Society), and Met-Bot for Disaster Surveillance (Royal Society). His recent publications emphasize privacy-preserving edge learning , semantic IoT data validation , and deep learning for weather prediction . As a supervisor, he has guided PhD students in areas like federated learning, smart building systems, and IoT security. Collaborations include partnerships with institutions in Scotland, China, and Italy, alongside funding from European Commission , Royal Society , and Scottish Funding Council . He contributes to international conferences and journals, with notable work in IEEE Transactions , ACM TAAS , and MDPI publications.
