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Dr. Oana Cocarascu is a Senior Lecturer in Artificial Intelligence at the Department of Informatics, Faculty of Natural, Mathematical & Engineering Sciences, King's College London. She holds a PhD and MEng in Computing (Artificial Intelligence) from Imperial College London and conducts applied research focusing on how artificial intelligence can be deployed to support real-world applications, with machine learning and natural language processing as core components of her work. Her research interests span argument mining, explainable AI, machine learning, natural language processing, and symbolic reasoning. She is particularly focused on developing AI systems that can provide transparent, accountable, and ethical decision-making processes. Her work addresses critical challenges in bias mitigation, fairness metrics, fact verification systems, and argumentation-based explanations for complex AI decisions. Analysis of her recent publications (2023-2025) reveals a strong focus on fairness in AI systems, with particular attention to individual fairness metrics and nuanced evaluation frameworks. She has made significant contributions to fact verification systems, especially in multimodal contexts involving charts and tabular data. Her work increasingly integrates argumentation theory with natural language processing to create explainable AI systems that can justify their decisions through structured reasoning. Dr. Cocarascu leads an EPSRC-funded project titled 'A framework for evaluating and explaining the robustness of NLP models' (2024-2027) and is actively involved in the Natural Language Processing Group at KCL. Her research fingerprint shows strong activity in argumentation (100%), decision-making (74%), artificial intelligence (50%), explainable AI (39%), and bias mitigation (35%). She has contributed to numerous high-impact publications in top venues including ACL, EMNLP, AAAI, and the Journal of Artificial Intelligence Research, with a particular focus on making AI systems more transparent, accountable, and aligned with human values. Her work intersects with UN Sustainable Development Goals, particularly those related to reducing inequality and building resilient infrastructure.

• Argument mining
• Explainable AI
• Machine learning
• +5 more

Andrew Rice is a Professor of Computer Science at the University of Cambridge's Department of Computer Science and Technology, and holds the Hassabis Fellowship in Computer Science. He is also the Director of Studies in Computer Science at Queens' College. His research focuses on programming languages, software engineering, and machine learning applications in software development. He leads projects like Isaac Computer Science and ALTA (Automated Language Teaching and Assessment), advancing adaptive learning technologies. His work includes static analysis tools such as Error Prone at Google, energy efficiency studies in computing infrastructure, and contributions to the Computing for the Future of the Planet initiative. His teaching emphasizes practical skill development through flipped classrooms and video lectures, earning him the 2014 Pilkington Prize for teaching excellence. He has held visiting roles at Google and collaborated on energy consumption research for mobile devices and data centers. His research spans systems, networking, and natural language processing, with a strong focus on applying computational methods to real-world challenges. Key Projects: Isaac Physics/Computer Science, ALTA, Error Prone Static Analysis Research Themes: Programming Languages, Machine Learning, Energy Efficiency Awards: Pilkington Prize (2014)

• Programming Languages
• Machine Learning
• Artificial Intelligence
• +4 more

Björn Ross is a Lecturer in Computational Social Science at the University of Edinburgh's School of Informatics, where he is affiliated with the Institute for Language, Cognition and Computation. He serves as Director of the SMASH research group and is part of the management team for the Centre for Doctoral Training in Natural Language Processing (CDT in NLP). His educational background includes: PhD (2019) from the University of Duisburg-Essen MSc in Computer Science (2016) from the University of Münster Exchange year (2014-2015) at the University of Strasbourg BSc in Information Systems (2013) from the University of Münster Ross's research focuses on computational social science, particularly using natural language processing, social network analysis, and agent-based modeling to study social media phenomena. His work examines misinformation, hate speech, bot activity, and the ethical implications of computational methods. He also investigates how social media can be leveraged for social good, especially in crisis communication contexts. A significant portion of his recent research addresses bias and fairness issues in AI systems, particularly regarding marginalized communities and LGBTQ+ identities. His work spans both technical development of computational methods and critical examination of their societal impacts. Analysis of his recent publications reveals a strong trend toward examining bias in AI systems, particularly regarding marginalized communities. His work spans multiple methodologies including computational analysis of social media data, development of NLP techniques, and critical examination of AI ethics. He frequently collaborates across disciplines, working with researchers in computer science, social sciences, and healthcare domains. His professional recognition includes: Best Paper Award at the Hawaii International Conference on System Sciences (HICSS) in 2018 Associate Editor for Business & Information Systems Engineering Active membership in professional organizations including AIS, ACL, and ACM Ross currently supervises multiple PhD students including Agostina Calabrese, Eddie Ungless, Sandrine Chausson, Wendy Zheng, Seraphina Goldfarb-Tarrant, and Mahmoud Ibrahim. At the University of Edinburgh, he teaches courses such as 'Text Technologies for Data Science' and 'Evidence, Argument and Persuasion in a Digital Age,' reflecting his expertise at the intersection of computational methods and social implications.

• Computational social science
• Social computing
• Information systems
• +9 more

Lukas Engelmann is a Senior Lecturer at the University of Edinburgh , specifically within the Science, Technology and Innovation Studies department under the School of Social and Political Science . His research focuses on the history and sociology of biomedicine , with particular interest in epidemiological reasoning , visual cultures of disease , digital epidemiology , and decolonial approaches to medical history . The Epidemy Lab , which he founded, explores the historical development of epidemiology and its contemporary influence on data-driven public health and pandemic policy-making . Engelmann's work has been funded by prestigious grants including an ERC Starting Grant (2021-2025) for his research on the history of epidemiological reasoning, and support from the Wellcome Trust for projects examining the social dimensions of digital health . His book 'Mapping AIDS' (2018) established him as a leading scholar in medical visualization , while 'Sulphuric Utopias' (2020) with Christos Lynteris explores the technological history of maritime sanitation and its political implications. Recent publications emphasize the visual and data practices that have shaped epidemiology, including works on epidemic modeling during the COVID-19 pandemic , the history of plague mapping , and the ethical implications of digital phenotyping . He has also contributed to interdisciplinary discussions on syndemics , co-infection epistemology , and the commercialization of bacteriology in the early 20th century. His scientific contributions have earned recognition through editorial roles in journals like Big Data and Society , and collaborative projects such as 'Working with Diagrams' (2022) which investigates the epistemological role of visual tools in medical knowledge production. Scientific Awards and Funding: ERC Starting Grant (2021-2025) Wellcome Trust Institutional Support Fund British Academy/Leverhulme Small Research Grant Chancellor's Fellowship (University of Edinburgh) 'Sulphuric Utopias' listed in The Guardian's 30 Books to Understand the World (2020)

• History of Epidemiology
• History of Science and Medicine
• Digital Health
• +7 more

Professor Claire Hardaker is a leading scholar in Forensic Linguistics at Lancaster University's School of Social Sciences. Her research focuses on aggression, deception, and manipulation in computer-mediated communication (CMC) for evidential and intelligence purposes. Research interests include: Corpus linguistics methodologies Online trolling and impoliteness Vaccine discourse analysis Forensic applications of linguistic analysis Current projects include: "Forensic linguistics, Cybersecurity and Technology Research: Operations Suite" (2023-2026) "Questioning Vaccination Discourse (Quo VaDis)" (2021-2024) Contact: c.hardaker@lancaster.ac.uk

• Forensic Linguistics
• Corpus Linguistics
• Computer-Mediated Communication
• +5 more

Dr. Kieran O'Halloran is a Reader in Applied Linguistics at King's College London, based in the School of Education, Communication & Society within the Faculty of Social Science & Public Policy. He holds a BA from the University of Cambridge and a PhD in Applied Linguistics from University College London. His research focuses on critical thinking, posthumanism, and digital pedagogy, integrating corpus linguistics and posthumanist theory. Key interests include creative teaching methods, digital text analysis, and the intersection of technology with education. He teaches modules such as 'Critical Posthumanism, Digital Data' and 'Film, Poetry, Style' in the BA English Language and Linguistics program. O'Halloran's work emphasizes innovative approaches to literary interpretation using AI and digital tools, as seen in his recent articles on AI-driven creative analysis and posthumanist stylistics. He leads initiatives like the King’s Festival of Artificial Intelligence, exploring AI's role in education and creativity. His research is affiliated with the Research Centre for Language, Discourse & Communication, focusing on descriptive linguistics and applied linguistic practices. Publications include books like Posthumanism and Deconstructing Arguments (2017) and Posthumanism and Corpus Linguistics (2022), alongside peer-reviewed articles in Language and Literature and Discourse, Context & Media . His pedagogical contributions highlight digital literacy and creative problem-solving in higher education.

• Critical Thinking
• Posthumanism
• Digital Humanities
• +4 more

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.

• Natural Language Processing
• Large Language Models
• Social Media Analysis
• +7 more

Dr Tommy Yuan is an Associate Professor (Reader) in the Department of Computer Science at the University of York. His research focuses on argumentation, dialogue systems, and AI applications in domains like social interaction for autistic children and railway systems. He holds a PhD in Computer Science and an MSc in Software Engineering. Education: PhD in Computer Science MSc in Software Engineering Research Interests: His work spans argumentation frameworks, machine learning techniques for argument mining, reinforcement learning for agent-based dialogue systems, and graph neural networks for argument labeling. He also explores AI's role in railway system dependability and assistive technologies for neurodivergent populations. Roles: Deputy Chair of Board of Examiners (On-campus) Member of StAMP Committee Contact: Email via departmental web form (ty513@york.ac.uk), Office CSE/141. Labs/Teams: Member of the Artificial Intelligence research group within the Department of Computer Science.

• Argumentation
• Dialogue Systems
• Natural Language Processing
• +4 more

Bjorn Ross is a Lecturer in Computational Social Science at the School of Informatics, University of Edinburgh. He is affiliated with the Institute for Language, Cognition and Computation and actively contributes to the Computational Social Science research area. He serves as Director of the SMASH research group and is part of the management team for the Centre for Doctoral Training in Natural Language Processing (CDT in NLP). Education: PhD, 2019, University of Duisburg-Essen MSc in Computer Science, 2016, University of Münster Exchange year, 2014–2015, University of Strasbourg BSc in Information Systems, 2013, University of Münster His research focuses on computational methods for analyzing social media, particularly using natural language processing, social network analysis, and agent-based modeling. Key interests include misinformation, hate speech, social bots, and the ethical implications of automated systems. He emphasizes fairness, bias, and data ethics in AI applications. His recent publications span topics such as queerphobic bias in sentiment analysis, explainable hate speech detection, temporal generalizability in misinformation models, and cross-lingual bias amplification. These works appear in leading venues including ACL, ICWSM, Social Science Computer Review, and Big Data & Society, reflecting a strong interdisciplinary focus bridging computer science, social science, and ethics. Scientific Awards: Best Paper Award, Electronic Government track, HICSS 2018 Ross supervises multiple PhD students and welcomes new applicants. He has also contributed to software tools and web-based platforms for argument analysis and counterspeech. He is an Associate Editor for Business & Information Systems Engineering and a member of AIS, ACL, and ACM. His teaching includes courses on Text Technologies for Data Science and digital persuasion. He leads the SMASH group, which focuses on social media analytics and societal challenges, and collaborates extensively within the CDT in NLP and the Institute for Language, Cognition and Computation.

• Computational Social Science
• Social Computing
• Information Systems
• +12 more

Xiang Yin is a Researcher at the Department of Computing, Faculty of Engineering, Imperial College London, specializing in Explainable AI (XAI) and Computational Argumentation (CA). His work focuses on Quantitative Bipolar Argumentation Frameworks (QBAFs) and their explainability. PhD in Computing, Imperial College London (2021-2025) MSc in Computer Technology, Beihang University (2017-2020) BSc in Computer Science and Technology, Hebei University of Technology (2013-2017) His research explores the integration of computational argumentation with AI systems to enhance transparency and interpretability. Key contributions include formal analysis of argumentation frameworks, counterfactual explanations, and attribution-based interpretability methods. Recent publications highlight his work on applying argumentation theory to large language models, truth-discovery mechanisms, and theoretical advancements in bipolar argumentation systems. These works span knowledge representation, machine learning, and human-AI collaboration frameworks. Xiang is affiliated with the Computational Logic and Argumentation group (CLArg) and the Argumentation-based Deep Interactive eXplanations (ADIX) project at Imperial College London. Contact: x.yin20@imperial.ac.uk .

• Explainable AI
• Computational Argumentation
• Artificial Intelligence
• +3 more

Praboda Rajapaksha is a Lecturer in Health Data Science at Aberystwyth University and a Data Scientist at HDUHB, NHS Wales. She holds a PhD in Computer Science from IP Paris, alongside advanced degrees from AIT (Thailand), IMT (France), and a B.Eng. from the University of Peradeniya, Sri Lanka. With over nine years of research experience, her expertise spans data science, natural language processing, generative AI, machine learning, and digital twin technologies. She leads the UKRI EPSRC-funded 'Portable Luminescent Chemical Compass' project and collaborates on the Welsh Government-funded 'DeepDetect' initiative. Education: PhD (IP Paris), M.Eng (AIT), M.Sc (IMT), B.Eng (Peradeniya) European Projects: ITEA, BPI, Horizon, FUI Her research focuses on applying AI to healthcare delivery transformation via Patient Digital Twins, traffic sensor optimization, and mitigating hallucinations in LLMs for sexism detection. Key areas include emotion analysis in arguments, cross-lingual hate speech detection, and unsupervised video anomaly frameworks. Recent work addresses redundancy reduction in sensor networks and emotion-aware meta-learning models. Scientific Contributions: 14+ peer-reviewed articles (2023-2025), conference proceedings Grants: EPSRC, Welsh Gov, EU initiatives Current projects include developing mobile diagnosis apps for agriculture and advancing IoT-enabled digital twin systems. Her work aligns with UN SDGs for health innovation and sustainable cities.

• Data Science
• Natural Language Processing
• Generative AI
• +7 more

Dr. Moritz Osnabrügge is an Associate Professor in Quantitative Comparative Politics at Durham University's School of Government and International Affairs. Previously affiliated with the London School of Economics, Bocconi University, and the University of Mannheim, he specializes in European politics and computational social science using advanced methods like natural language processing, machine learning, and experiments. Research focuses: Political competition, representation, rule of law, legislative decision-making Expertise: Quantitative methodology, computational social science, EU policy analysis His recent work analyzes legislative quality, political rhetoric, and public opinion dynamics across Europe. Current British Academy/Leverhulme-funded project on legislative decision-making processes. Actively supervises PhD students including Edward Zeng, with notable contributions to journals like Political Science Research and Methods , American Political Science Review , and Political Analysis .

• European politics
• Computational social science
• Natural language processing
• +7 more

Rob Alexander is a Senior Lecturer in the Department of Computer Science at the University of York. He holds a BSc from Keele University (2001) and a PhD in Computer Science from the University of York (2008). His research focuses on safety analysis and testing of autonomous robots and multi-agent systems, including simulation methods for hazard analysis and empirical evaluation of safety engineering techniques. He is part of the High Integrity Systems research group. Key research interests include situation coverage-based safety analysis, autonomous systems verification, and safety assurance methodologies. His work spans robotics, autonomous vehicles, and safety-critical systems, with applications in mine environments, healthcare, and transportation. Recent publications emphasize rigorous testing frameworks, risk assessment in complex systems, and bridging theoretical and practical safety engineering challenges. No scientific awards or grants are explicitly listed. He serves as a Union Rep within the department and is involved in academic leadership roles. His research group collaborates on projects such as SCALOFT and SASSI, focusing on safety assurance in autonomous systems.

• Safety Analysis of Autonomous Systems
• Multi-Agent Systems
• Hazard Analysis Simulation
• +3 more

Professor Andrew Ravenscroft is a Professor of Education and Social and Community Work and Senior Research Advisor at the University of East London, working within the School of Childhood and Social Care and the Department of Social Work Counselling & Social Care. He serves as the Cluster Professor covering Social and Community Work programmes at undergraduate and postgraduate levels. As a Chartered Psychologist (C.Psychol), Associate Fellow of the British Psychological Society (AFBPsS), and Fellow of the RSA (FRSA), he maintains active roles in the Centre for Wellbeing, Community and Inclusion; the Centre for Social Change and Justice; and as an Associate of the Institute for Connected Communities (ICC). Dr. Ravenscroft's research focuses on interdisciplinary approaches to Psychosocial and Socio-technical Innovation in educational and community settings. His work spans inclusive education, mental health and wellbeing, criminal exploitation of vulnerable children and youth violence, mindfulness-based interventions, and the development of inclusive thinking dialogue through technology design. He has developed innovative approaches such as the RadioActive101 project, which uses participatory internet radio to promote inclusion and non-formal learning among disenfranchised youth, and the Boxing and Mindfulness (BAM) program as an early intervention for mental health. His publication portfolio demonstrates a consistent trajectory toward social innovation through technology, with particular emphasis on community engagement, participatory media, and interdisciplinary approaches to addressing social exclusion. The research shows strong connections between educational technology, psychological wellbeing, and community development, with a clear focus on vulnerable populations and innovative intervention methodologies. Chartered Psychologist (C.Psychol) Associate Fellow of the British Psychological Society (AFBPsS) Fellow of the RSA (FRSA) Winner of the international 'digging into data challenge' 2011 Professor Ravenscroft has attracted over £6.46 million in research funding throughout his career, serving as Principal or Co-Investigator on numerous projects. He supervises doctoral students working on topics ranging from digital inclusion to youth mental health and mathematics achievement. His current projects include RadioActive 2.0, BAM (Boxing and Mindfulness), and research on toxic childhood conditions. He has also been instrumental in developing the Westfield Opening Observation Exercise for the London 2012 Olympic Games and collaborating with organizations like Ridiculusmus Theatre Company on mental health awareness initiatives. His work bridges academic research with practical community applications, particularly through his leadership of the RadioActive projects across multiple European countries and his academic role in the Newham Youth Safety Action team (NYSAT). Ravenscroft maintains strong connections with Buddhist meditation practices, which inform his mindfulness-based research approaches.

• Critical and inclusive education
• Socio-technical innovation
• Psychosocial innovation
• +6 more

Richard Gomer is a Lecturer in Computer Science at the University of Southampton, affiliated with the Web, AI and Society research group. He holds a BSc, MSc, and PhD in Computer Science from Southampton. His research focuses on Human-Computer Interaction (HCI), particularly how individuals and groups interact with large-scale systems and the role of values and agency in design. Education: BSc Computer Science (University of Southampton), MSc Web Science (via Web Science Doctoral Training Centre), PhD examining values in Privacy/Data Protection and Personal Fitness Devices. Research Interests: Human-Computer Interaction, Agency-oriented Design, Data Institutions, Consent & Privacy. His work explores topics like participatory budgeting, mobility systems, and ethical design in wearable technology. Recent projects include CivicMAGIC (mobility futures) and QROWD (human-AI collaboration in transportation data). Teaching: Leads COMP2213 (Interaction Design), COMP3227 (Web Architecture), and COMP6250 (Social Media & Network Science). Supervises PhD students in areas like Web Science and Politics. External Roles: Member of World Economic Forum Taskforce on Data Intermediaries (2020-2021), Councillor for Eastleigh Borough Council (West End North ward), and Chair of the Policy and Performance Scrutiny Panel. Labs/Teams: Active in the Web and Internet Science research group and the Agents, Interaction and Complexity cluster.

• Human-Computer Interaction
• Agency-oriented Design
• Data Institutions
• +4 more