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Walid Magdy is a Professor at the School of Informatics, The University of Edinburgh, where he is a faculty member at the Institute for Language, Cognition and Computation (ILCC). He holds a PhD from Dublin City University's School of Computing and has been a faculty fellow at The Alan Turing Institute. With substantial industry experience, he has worked for Qatar Computing Research Institute (QCRI), Microsoft, and IBM, where he filed nine patents. His research spans computational social science and natural language processing. In computational social science, he focuses on social content analysis, political bias detection, polarization, and users' behavior analysis/prediction, with particular attention to understudied communities. His natural language processing work centers on social applications including sentiment analysis, sarcasm detection, and hate-speech identification, with specialized expertise in Arabic and its dialects as well as Persian. Professor Magdy's recent publications demonstrate a consistent focus on Arabic language processing and social media analysis, with growing attention to cultural factors in NLP systems. His work bridges computational methods with social science questions, particularly regarding misinformation, cultural differences in online behavior, and the impact of platform policies on diverse linguistic communities. He has expanded his research to include Persian language processing and continues to explore social dynamics across different cultural contexts. His significant contributions have been recognized with multiple awards: Best Demo Award for TwiXplorer at CSCW 2024 Outstanding Paper Award at ACL 2024 Best Paper Award Runner-up at SocInfo 2022 Best Paper Award at WANLP-EMNLP 2022 Best Paper Award at AIRS 2015 Best Dataset Award at ICWSM 2013 Professor Magdy serves as an editor for Springer's Social Network Analysis and Mining journal and has held leadership roles in major conferences including ACL 2023, ArabicNLP 2023, ICWSM 2022, and ASONAM 2022. He has co-organized numerous shared tasks focused on Arabic language processing and social media analysis, contributing significantly to community resources and benchmarks. He founded and directs the Social Media Analysis and Support for Humanity (SMASH) research group at the University of Edinburgh, which has organized the Summer School in Computational Social Science (SICSS-Edinburgh) in 2022, 2023, and 2025, training researchers in computational social science methodologies.

• Computational Social Science
• Natural Language Processing
• Social Content Analysis
• +8 more

Dr. Matloob Khushi serves as a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. With over 25 years of combined academic and industry experience, his work bridges theoretical AI advancements with practical applications in finance, healthcare, and public health domains. His research has established significant collaborations with international banks, healthcare institutions, and technology startups. Dr. Khushi earned his PhD in AI and Data Science from the University of Sydney, developing novel algorithms for genomic data analysis. His postdoctoral research at the Children's Medical Research Institute (2014-2017) pioneered AI-based diagnostic tools for medical condition detection. More recently, he developed bioinformatics tools for environmental assessment under a UKRI NEC grant. Research Focus FinTech Innovation : Creator of the SS Ratio (incorporating volatility and drawdown sensitivities), advanced portfolio optimization models, and synthetic data generation techniques for fraud detection and credit risk assessment Bioinformatics Leadership : Developer of AI tools for genomic analysis and early cancer detection, featured in SBS News and The Daily Telegraph Public Health NLP : Architect of systems for vaccine misinformation detection, mental health monitoring, and health surveillance on social media His publication portfolio shows consistent growth from foundational bioinformatics work to current multimodal AI applications, with increasing interdisciplinary collaboration across finance and healthcare sectors. Awards and Recognition Ranked among Stanford/Elsevier's top 2% of global AI scientists Recipient of Best Paper Awards from IEEE Transactions on Computational Social Systems and PeerJ Media recognition for cancer detection research by major news outlets Mentorship and Teaching Dr. Khushi has supervised six PhD candidates to completion and over 100 postgraduate dissertations. He teaches CS3002 Artificial Intelligence and mentors students in Final Year Projects. His supervision focuses on Deep Learning/NLP for FinTech prediction and Public Health Surveillance applications, emphasizing practical implementation of theoretical concepts.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +7 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

Blake Miller is an Assistant Professor of Computational Social Science in the Department of Methodology at the London School of Economics (LSE), affiliated with the Data Science Institute. Their research focuses on computational methods applied to political communication in authoritarian regimes, particularly China, and the intersection of social media with political violence and identity politics. They hold a PhD from the University of Michigan (2018) and conducted postdoctoral research at Dartmouth College. Key substantive areas include: China's surveillance-driven security state and information control mechanisms Political mobilization through moral outrage and outgroup targeting Technological adaptations in authoritarian governance Methodological expertise spans machine learning, text analysis, and fairness in AI applications. Their book project Platforms and Power examines how authoritarian states delegate censorship to private platforms. Teaching focuses on quantitative text analysis and machine learning in political contexts. Research outputs include influential work on: Censorship patterns during China's zero-COVID protests Moral-emotional triggers for violence support Evaluation of active learning algorithms for text labeling Blake's work has been featured in The Washington Post , China File , and the CSIS Pekingology Podcast. They maintain an active presence in interdisciplinary research communities.

• Computational Social Science
• Text Analysis
• Social Media Politics
• +7 more

Dr Scott A. Hale is an Associate Professor and Senior Research Fellow at the Oxford Internet Institute (OII), University of Oxford, and a Fellow of the Alan Turing Institute. His work bridges computer science and social sciences, focusing on equitable information access, multilingual online dynamics, and misinformation mitigation. He holds degrees in Computer Science, Mathematics, and Spanish from Eckerd College, followed by a DPhil (PhD) in Social Data Science from the OII. Hale’s research has been supported by grants from UK Research and Innovation, the US National Science Foundation, and organizations like the Omidyar Network and the Alan Turing Institute. Key Roles: Programme on AI, Government & Policy; Director of Research at Meedan; Co-Director of the Social Data Science MSc Research Focus: Misinformation, multilingual systems, social media impact, and AI ethics Education: Eckerd College (BS), OII (MSc, DPhil). His DPhil explored social media design’s role in cross-language information sharing. Recent projects include the Digital Good Network and AI alignment studies. Articles highlight trends in multilingual misinformation detection, LLM cultural biases, and hate speech dynamics. Hale’s work bridges technical innovation with social science rigor to address global digital challenges. Awards: Alan Turing Institute Fellowship, recognition in Oxford’s Teaching Excellence Awards. Grants: Over 20 funding sources including DSO National Laboratories and Meta.

• Human-Computer Interaction (HCI)
• Machine Learning
• Natural Language Processing (NLP)
• +7 more

Dr. Shweta Singh serves as an Assistant Professor of Information Systems and Management at Warwick Business School, University of Warwick. She concurrently holds prestigious appointments as a Fellow at the Warwick Institute for Global Sustainability Development (IGSD) and a Behavioral Data Science researcher at The Alan Turing Institute in London. Her academic journey includes a Ph.D. in Information and Decision Sciences from the Carlson School of Management at the University of Minnesota, complemented by dual Master's degrees in Computer Science and Applied Economics from the same institution. Ph.D. in Information and Decision Sciences, University of Minnesota Master's in Computer Science, University of Minnesota Master's in Applied Economics, University of Minnesota Dr. Singh's research centers on developing ethical and responsible artificial intelligence systems that address societal challenges. Her work specifically targets mitigating AI bias, creating explainable AI frameworks, and leveraging technology to combat societal injustice. She investigates how digital platforms, sharing economy models, and IT outsourcing create business value while ensuring these technologies promote sustainability and reduce inequalities. Her innovative approach combines technical AI expertise with deep social awareness, particularly focusing on gender equality and child protection in digital spaces. Her publication record demonstrates consistent high-impact contributions to Information Systems Research, International Conference on Information Systems, and related venues. The trajectory of her work shows increasing focus on practical applications of responsible AI, with recent projects addressing online child safety and human trafficking prevention. Her research increasingly intersects with policy development, as evidenced by her contributions to UK Parliamentary Office of Science and Technology briefs. Doctoral Dissertation Fellowship, University of Minnesota McNamara Fellowship, University of Minnesota Social Impact Project of the Year shortlist (2023) Asian Women of Achievement Award finalist (2023) British Indian Awards finalist (2019) Top 5 Women in Tech for Good Award shortlist (2022) Inspiring 50 UK recognition (2025) Dr. Singh actively mentors students and has been recognized with the Staff Social Inclusion Award (2024) for her teaching excellence. Her advisory roles extend beyond academia to include the UN Women UK delegation for the Commission on the Status of Women and the Advisory Board of AI retail company 'Love the Sales'. She serves as an external collaborator for Boston Consulting Group's Henderson Institute, bridging academic research with industry applications. Through her leadership in the ISM-Analytics (ISMA) Group at Warwick, Dr. Singh fosters interdisciplinary collaboration focused on creating socially responsible technological solutions. Her work with the IGSD specifically targets UN sustainability goals related to reducing inequalities and promoting inclusive societies through responsible AI implementation.

• Artificial Intelligence
• Responsible AI
• Explainable AI
• +7 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

Dr. Mo El-Haj is a Reader (Associate Professor) in Natural Language Processing (NLP) at the College of Engineering & Computer Science, VinUniversity, Hanoi, Vietnam, and holds a visiting role at Lancaster University. He specializes in NLP with a focus on Financial NLP, Arabic NLP, and multilingual systems for under-resourced languages. Education: PhD in Computer Science (University of Essex, 2012), MSc in Information Systems (University of Jordan, 2008), BSc in Computer Information Systems (University of Jordan, 2005). Awards include the FHEA Fellowship (2021) and the 2016 BBC NewsHack Best Tool award. Research interests include text summarization, financial narrative processing, biomedical NLP, and corpus linguistics. He leads the VinNLP research group and has supervised/co-supervised over 20 PhD students. Notable projects include the Welsh Automatic Text Summarisation tool (ACC) and the FreeTxt bilingual analysis toolkit, funded by the Welsh Government and AHRC. Publications span 92+ works in top journals/conferences like Computational Linguistics and LREC. Active in organizing workshops (e.g., WACL-4, FinNLP) and has served as external/internal PhD examiner at UK universities.

• Natural Language Processing
• Financial NLP
• Arabic NLP
• +9 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

Haim Dubossarsky is a Lecturer in Computer Science at the School of Electronic Engineering and Computer Science , Queen Mary University of London , and an Affiliated Lecturer at the Language Technology Lab , University of Cambridge. His work bridges Natural Language Processing (NLP) , Artificial Intelligence (AI) , and interdisciplinary studies in linguistics , cognitive neuroscience , and mathematical modeling . Dr. Dubossarsky's research explores semantic change and language variation through computational methods, focusing on: Detecting historical and contemporary linguistic shifts Integrating neurocognitive insights into NLP systems Developing interpretable AI models for language tasks Recent publications highlight his contributions to multilingual NLP , word-in-context (WiC) tasks , and robust semantic analysis . His work includes collaborations on hate speech detection , topological representations , and temporal modeling in language evolution. Dr. Dubossarsky leads projects funded by: UKRI AI Hub (£1,026,205, 2024–2029) RJ Riksbankens Jubileumsfond (£381,511, 2022–2027) Innovate UK (£320,887, 2024–2025) He supervises PhD students at Queen Mary's Centre for Human-Centred Computing , including Alaa Bazaid , Roksana Goworek , and Dina Pisarevskaya , working on topics like multilingual polysemy disambiguation and language variation analysis .

• Natural Language Processing
• Artificial Intelligence
• Historical Linguistics
• +3 more

Dr. Priyanka Chaurasia is a Lecturer in Data Analytics at the School of Computing, Engineering and Intelligent Systems, Ulster University, based in the Derry~Londonderry campus. Her research focuses on machine learning applications in healthcare, cybersecurity, and assistive technologies. She contributes to interdisciplinary projects such as the EU-funded 'IT4Anxiety' mental health initiative and has expertise in AI-driven solutions for lead toxicity prediction, smart city security, and Metaverse privacy frameworks. Her academic background includes a strong emphasis on data science, with notable work in IoT security, medical image segmentation, and regulatory frameworks for large language models. She has collaborated on projects addressing technology adoption by older adults and individuals with dementia, emphasizing ethical AI and user-centric design. Dr. Chaurasia's recent publications span topics like deep learning for hate speech detection, privacy-preserving techniques in virtual environments, and computational modeling for environmental health risks. She maintains an active research profile, publishing in top-tier venues and co-authoring over 40 peer-reviewed articles since 2010. Her lab focuses on bridging theoretical advancements with practical healthcare and cybersecurity solutions.

• Machine Learning
• Data Analytics
• Cybersecurity
• +5 more

Diana Galvan Sosa is a Researcher at the University of Cambridge, affiliated with the ALTA Institute (Automated Language Teaching and Assessment) and the NLIP group. She holds a doctoral degree in Information Science from Tohoku University (Japan). Her research focuses on Natural Language Processing (NLP), particularly knowledge acquisition and applications of NLP in education, including feedback generation systems for second language (L2) learners. She also contributes to clinical text analysis and hate speech detection research. Education: PhD in Information Science from Tohoku University, Japan. Research Interests: Grammatical Error Correction Educational Technology Clinical NLP Explainability in AI Temporal Relation Extraction Multimodal Reasoning Recent Work Trends: Her most recent publications (2023-2025) emphasize advanced NLP applications like GPT-4 analysis for error correction, hate speech detection leveraging platform guidelines, and evaluation frameworks for AI explanations. Earlier work includes foundational studies on clinical text analysis and addiction treatment populations. Labs/Groups: Active member of the ALTA Institute and NLIP group at Cambridge. Also contributes to open-source projects like the GECToR framework for grammatical error correction, reflected in her GitHub repositories.

• Natural Language Processing
• Knowledge Acquisition
• Applications of NLP in Education
• +3 more

Professor Maura Conway holds a 0.2FTE position at Swansea University and is concurrently a Professor of International Security at Dublin City University (DCU). She is the founding Coordinator of the VOX-Pol research network, specializing in analyzing online extremism, cyber-terrorism, and counter-terrorism strategies. Her work bridges academic research with policy impact, having presented at the UN, EU Commission, and UK House of Lords. Roles: Professor of Cyber Threat Innovation (Swansea) and Professor of International Security (DCU) Key Affiliations: Europol Counter-Terrorism Center Academic Advisory Board, Editorial Board of Terrorism and Political Violence Her research focuses on the intersection of terrorism and digital technologies, including violent online radicalization and extremist content moderation. Recent projects include analysis of far-right online ecosystems and ethical frameworks for extremism researchers. Notable collaborations include work with Global Internet Forum to Combat Terrorism (GIFCT), NATO, and the EU’s Horizon 2020 programs. She has secured grants totaling over €5 million for initiatives like VOX-Pol and counter-narrative development. Supervising a PhD on gender dynamics in contemporary far-right movements, she emphasizes interdisciplinary approaches to understanding and countering extremist ideologies.

• Online Terrorism
• Cyber terrorism
• Online Radicalization
• +3 more

Diyi Liu is a DPhil candidate in Information, Communication, and the Social Sciences at the University of Oxford’s Oxford Internet Institute (OII). Her research focuses on platform governance, particularly examining algorithmic content moderation and the legitimacy of speech governance in South and Southeast Asia. She holds multiple visiting and research fellow roles, including at the National University of Singapore, Weizenbaum Institute, CSIS Jakarta, and Tech Global Institute. Her work bridges policy, technology, and societal impacts, with publications in journals like Policy & Internet and New Media & Society . Education: Diyi earned her BA and MA in International Journalism and Communication in China before pursuing her DPhil, funded by the prestigious Clarendon Scholarship. Her academic trajectory emphasizes interdisciplinary research, combining communication theory with computational methods. Research Interests: Platform governance, human-centred computing, communication law and policy, political communication, and computational methods. Her work often addresses ethical challenges in digital platforms and the intersection of policy with user experiences. Publications: Recent articles explore global hate speech datasets, decentralized social media governance (e.g., Mastodon), and health misinformation dynamics. Her research emphasizes actionable insights for policymakers and platform administrators. Awards: Recipient of the Clarendon Scholarship, supporting her doctoral studies. Her contributions to UNESCO’s pilot research on Thailand’s digital governance further highlight her engagement with multistakeholder initiatives. Professional Activities: Engaged with initiatives like the UNESCO Internet Universality Indicators and the Guidelines for the Governance of Digital Platforms. She actively communicates research through media outlets like The Diplomat and collaborates across institutions in Asia, Europe, and beyond.

• Platform governance
• Human-centred computing
• Communication law and policy
• +2 more

Sarah Glozer is a Professor and Head of Marketing in the Business & Society Division at the University of Bath School of Management. She holds affiliations with the Centre for Business, Organisations and Society (CBOS), the Centre for Qualitative Research, and the Centre for the Future of Work. Her research focuses on responsible business communication in digital contexts, particularly influencer marketing, content moderation, and ethical advertising. She co-authored a leading European Business Ethics textbook and serves on the editorial board of Business & Society . Education: PhD in Corporate Social Responsibility Communication from the University of Nottingham (2014), Fellow of the Higher Education Academy from Royal Holloway, University of London (2015). External roles include External Examiner at ESCP Business School (2018–2023). Recent projects include leading the 7th International CSR Communications Conference (2024), studying content moderation’s human rights implications, and exploring platform responsibility in influencer marketing. Current research areas emphasize digital ethics, stakeholder dialogue frameworks, and sustainable development goals. Key projects include: "Bringing Consumers Back Down to Earth" (ecstatic dance wellness project) "Content Moderation: Interdisciplinary Insights" (2021–2022) "Platform Responsibility and Influencer Marketing" (2020–2024) Her work contributes to UN Sustainable Development Goals related to quality education, decent work, and climate action. Over 47 peer-reviewed publications span journals like Business & Society , Journal of Business Ethics , and Organization Studies .

• Corporate Social Responsibility (CSR) Communication
• Digital Ethics
• Sustainability
• +3 more