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Anna Rohrbach is Full Professor of Multimodal Grounded Learning at TU Darmstadt and hessian.AI. Previously at UC Berkeley, she earned her PhD from Max Planck Institute for Informatics. Her research integrates computer vision and natural language processing, including video description, visual question answering, text-to-image synthesis, and multimodal forensics. She develops explainable models addressing bias and language-guided learning. Awards: DAGM German Pattern Recognition Award (2023) Leadership: Area Chair for ICCV/CVPR, organizer of CLVL workshop Recent work focuses on fact-checking systems (DEFAME) and geolocation AI (G^3).

• Computer Vision
• Natural Language Processing
• Multimodal AI
• +3 more

Dr. Aviv Barnoy is an Assistant Professor at the Department of Media and Communication within the Erasmus School of History, Culture and Communication (ESHCC) at Erasmus University Rotterdam. His research focuses on strategic communication, digitalization, AI epistemology, and misinformation studies, blending philosophical theories with empirical analysis. He actively collaborates with industry, regulators, and citizens to bridge academic and practical domains. Barnoy’s work has been supported by grants from the International Communication Association (ICA), Israel Science Foundation (ISF), and other institutions. His interdisciplinary research examines contemporary challenges in media trust, journalistic practices, and the epistemological foundations of news production. He frequently engages with national media to contextualize complex issues for public discourse. Research Grants: ICA, ISF, Komorov Fund, The 2nd Authority for Media, Zefat College Fund, AiPact Key Themes: Media Cynicism, Native Advertising Boundaries, Epistemic Crisis in Journalism His publications explore topics such as verification processes, source credibility dynamics, and the evolution of news ecosystems. Barnoy’s methodological contributions include innovative approaches to reconstructing news production practices, offering frameworks for understanding modern journalism’s complexities.

• Strategic Communication
• Digitalization
• AI Epistemology
• +3 more

Dr. H.H. (Vivian) Chen is Associate Professor in the Department of Media and Communication at Erasmus School of History, Culture and Communication (ESHCC), Erasmus University Rotterdam. Her work explores how interactive digital media—AI, VR, games, and social platforms—shape communication behaviors, identity negotiation, and intergroup relations. Research Interests: Social & psychological effects of AI, virtual reality, and video games Avatar embodiment, self-esteem, and identity construction Intergroup contact, prejudice reduction, and prosocial game design Online toxicity, moral choices in games, and streaming media psychology Immersive technologies for learning and cultural heritage Across 2025-2021 publications she interrogates AI misinformation, metaverse communication, avatar personalization, toxic gaming behavior, and empathy-driven VR interventions, positioning her scholarship at the intersection of communication science, media psychology, and human-computer interaction. Institutional Contact: chen@eshcc.eur.nl Dr. Chen currently participates in the €6.8 million DECIDE consortium (2025) aiming to democratize AI decision-making, underscoring her commitment to interdisciplinary, societally engaged research.

• Communication Science
• Media Psychology
• Interactive Digital Media
• +8 more

Andrew Fano is a Clinical Professor of Computer Science at Northwestern University and serves as the McCormick Director of the Kellogg-McCormick MBAi Program. He previously spent 25 years at Accenture Labs as Global Managing Director for AI Research, leading global teams in applied AI projects across industries like healthcare, retail, and pharma. His research focuses on combining emerging AI technologies with human capabilities to solve industry-specific challenges, with notable contributions in causality detection, quantum computing, and responsible AI deployment. Fano is a top patent holder at Accenture, emphasizing practical AI applications and ethics. He also led the Accenture Labs University program, fostering academic-industry collaborations. Education: PhD in Computer Science, Northwestern University AB in Cognitive Science, Vassar College His research interests span causal reasoning in NLP, AI ethics, and cross-industry AI integration. Recent work includes analyzing diabetes-related social media for causal insights and developing quantum optimization systems. He prioritizes real-world applicability, ensuring technologies address practical business and societal needs responsibly. Awards: None explicitly listed, though recognized as a top patent holder at Accenture. Advising & Grants: Advised on multiple AI projects across industries, coordinated research sponsorships with 20+ universities through Accenture Labs. At Northwestern, leads the MBAi Program to bridge academic and corporate AI expertise. Labs/Teams: Oversees the MBAi Program’s interdisciplinary initiatives and previously managed global AI research teams at Accenture Labs, collaborating with partners in the US, Ireland, India, China, and France.

• Artificial Intelligence
• Machine Learning
• Applied Artificial Intelligence
• +7 more

Jeremy Bowles is an Assistant Professor in Political Science and Public Policy at University College London. His research focuses on political economy in sub-Saharan Africa, examining elections, misinformation, and state-building. He earned his Ph.D. from Harvard University and was a Postdoctoral Fellow at Stanford's King Center. Research explores how information shapes political behavior and economic outcomes, with field experiments in Liberia, Zimbabwe, and South Africa. Projects investigate voter information access, fact-checking efficacy, and taxation systems.

• Political Economy
• Development Economics
• Sub-Saharan Africa
• +2 more

Dr. Henry Kudzanai Dambanemuya is an Assistant Instructional Professor in the Masters in Computational Social Science (MACSS) program at the University of Chicago. His teaching focuses on computational methods, research design, and elective topics like collective intelligence and digital peacebuilding. He holds a multidisciplinary background spanning computer science, communication, and international peace studies, leveraging software engineering expertise from roles at Microsoft and other tech firms. Education B.A. in Computer Science and Conflict Studies (DePauw University) M.A. in International Peace Studies (University of Notre Dame) M.Sc. and Ph.D. in Technology and Social Behavior (Northwestern University) Research Interests His work integrates Big Data mining, machine learning, and network science to study collective intelligence in complex systems. Key areas include: - Crowdfunding dynamics and signaling mechanisms - Online discourse analysis and influence networks - Humanitarian aid monitoring via multilingual datasets (HumVI) - Stress detection using wearable biosensors (HealthSense) - Peace process implementation through network analysis Grants & Advising While specific grants aren't listed, his industry collaborations (RICS Software, Dataminr) and academic partnerships (ACM, IEEE) suggest active funding. He advises MACSS students on balancing academic and industry career paths. Labs & Teams Active in computational social science research communities, with ongoing collaborations at WebSci, CHI, and ICWSM conferences. Maintains a public research portal for current projects.

• Computational Social Science
• Network Science
• Social Computing
• +6 more

Yulong Chen is a Researcher at the Department of Computer Science and Technology, University of Cambridge. He specializes in Natural Language Processing (NLP), focusing on areas such as large language models (LLMs), constituency parsing, cross-lingual summarization, and dialogue systems. His work bridges theoretical advancements with practical applications, including automated claim verification, multimodal intelligence, and ethical AI considerations. Chen contributes to both teaching and research: he teaches courses on Natural Language Processing at both undergraduate and postgraduate levels. His research emphasizes interdisciplinary approaches, combining machine learning, computational linguistics, and cognitive models. Key projects include developing benchmarks for higher-order theory of mind reasoning in LLMs and designing frameworks to uncover model weaknesses. His publications span foundational surveys (e.g., on LLM hallucinations and text-to-SQL systems) to applied work like MACSum for controllable summarization and Hi-TOM for evaluating social cognition in AI. He collaborates extensively on tools like EASE for efficient data annotation and UniSumm for few-shot summarization, reflecting his commitment to advancing both NLP infrastructure and model capabilities.

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +6 more

Zhenyun Deng is a Researcher in the Department of Computer Science and Technology at the University of Cambridge, specializing in Natural Language Processing (NLP) and Machine Learning. His work focuses on advancing automated fact-checking systems, logical reasoning in large language models, and graph-based reasoning techniques. Key research themes include document-level claim extraction, logic-driven data augmentation, and multi-hop question answering. His recent contributions span automated verification of textual claims , abstract meaning representation-based data augmentation , and robust node classification on graph data . He collaborates on initiatives like the FEVER workshop and develops datasets such as TaKG for table-to-text generation enhanced with knowledge graphs. Notable trends in his publications include: Integration of logical reasoning into NLP systems Improving model interpretability for multi-step reasoning tasks Handling noisy data in graph neural networks His research bridges foundational machine learning theory with real-world applications in information retrieval and causal inference. No awards or grants are explicitly listed in the provided materials.

• Natural Language Processing
• Machine Learning
• Logical Reasoning
• +7 more

Dr. David Yarrow is a Lecturer in Political Economy at the University of Edinburgh's School of Social and Political Science. His research focuses on the interplay between economic ideas, governance, and structural power dynamics in advanced capitalism. He examines topics such as digital capitalism, automation, environmental accounting, and the political economy of forecasting. Research Interests: International Political Economy Constructivism Politics of Economic Ideas Global Environmental Accounting Macroeconomic Modelling Digital Technologies and Labour Markets Recent work explores how economic ideas shape policy responses to crises like climate change, demographic shifts, and automation. His publications analyze structural power dynamics, green markets, and the governance of systemic risk through lenses of ideational continuity and institutional frameworks. Key Themes in Articles: Dr. Yarrow’s articles critically engage with the boundaries between economy and environment, the role of technocratic governance in macroeconomic policy, and the implications of digital technologies for capitalist systems. He emphasizes the normative dimensions of economic discourse in a post-truth era, questioning how measurement practices influence political decisions. Lab/Research Groups: He is affiliated with the International Political Economy Research Group and Work & Economy thematic area, contributing to interdisciplinary discussions on digital capitalism and sustainable development.

• International Political Economy
• Comparative Political Economy
• Constructivism
• +5 more

Smaranda Muresan is an Associate Professor in the Department of Computer Science at Barnard College, Columbia University. She is also an Affiliate Faculty in Columbia's Department of Computer Science and a member of the Data Science Institute (DSI). Her research focuses on human-centric Natural Language Processing (NLP) for social good and responsible computing, emphasizing theory-guided and knowledge-aware computational models for understanding and generating language in diverse contexts. Key research areas include argument mining, fact-checking, figurative language processing, multilingual NLP for low-resource languages, and explainable AI. Before joining Barnard in 2024, she was a Research Scientist at Columbia's Data Science Institute and a faculty member at Rutgers University's School of Communication and Information, where she co-founded the Laboratory for the Study of Applied Language Technologies and Society. She earned a Distinguished Achievements in Research Award during her time at Rutgers. Muresan has led significant grants, including NSF-funded projects on fine-grained visual classification with text and images, and reducing STEM achievement gaps using NLP. She is also a Technical Lead in DARPA's DEFT Program for detecting contradictions in text and speech. Her teaching includes undergraduate and graduate courses in NLP, multilingual technologies, and computational models of social meaning. She actively contributes to professional activities, including workshops on figurative language processing and argument mining.

• Natural Language Processing
• Social Good
• Responsible Computing
• +9 more

Bente Kalsnes is a Professor at the Department of Communication, Kristiania University of Applied Sciences. She specializes in political communication, digital journalism, and disinformation research. Her work focuses on social media's impact on politics, platform governance, and AI's role in information verification. Education: PhD from the University of Oslo's Department of Media and Communication. Previously worked as an Associate Professor at OsloMet and held roles in journalism and communications. Research Interests: Political use of social media, fake news, platform power, and AI ethics. Her book Fake News: Lies, Disinformation and Propaganda in the Digital Public Sphere (2019) critically examines disinformation dynamics. Grants & Projects: Co-editor of Norsk medietidsskrift (2020-2023), participant in the SCAM research project (2020-2024), and member of the Norwegian government’s Expert Group on AI and Elections (2024-2025). Expert Roles: Served on the Freedom of Expression Commission (2020-2022) and the Nordic Think Tank for Democracy and Technology (2022-2023). Publications: Contributed to New Media & Society , Digital Journalism , and co-edited the Routledge Handbook of Political Campaigning (2024). Her recent work addresses AI in fact-checking, platform policies during political events, and Nordic approaches to tech governance.

• Political Communication
• Digital Journalism
• Disinformation Studies
• +3 more

Zhu (Drew) Zhang is a Courtesy Associate Professor at the Department of Information Systems and Business Analytics, Ivy College of Business, Iowa State University. He holds a Ph.D. in Information and Computer Science from the University of Michigan (2005) and has professional experience at IBM, Microsoft, and Google. His research focuses on computational models for textual data, including AI, machine learning, and big data applications in business and healthcare. He also explores data/text/web mining and semantic analysis techniques. Dr. Zhang’s expertise spans artificial intelligence, big data analytics, and text mining. He has been recognized with the 2015 Schulze Award for his contributions. His work bridges theoretical research and practical applications, emphasizing real-world relevance in teaching and industry collaboration. Key research trends in his articles include advancements in dialog systems, financial forecasting using news data, and biomedical text analysis. His publications reflect a strong focus on integrating computational methods with domain-specific challenges in business and healthcare. While no lab affiliations are explicitly mentioned, his collaborative projects likely involve interdisciplinary teams given his research scope.

• Artificial Intelligence
• Machine Learning
• Data Science
• +7 more

Mrinalini Singha is a Professor at MIT's Schwarzman College of Computing and concurrently pursues an MS in Art, Culture, and Technology. Her work bridges creative practice with socio-ethical computing research, focusing on climate justice, decolonial perspectives, and interactive technologies. She leads the Worlding project (MIT Open Documentary Lab/Unity) exploring game engines for climate futures visualization and co-created the award-winning A Mystery for You fact-checking game (ACM CHI’24). Education: B.Des from National Institute of Design (India), Ford Foundation Fellow (2020-2021), and Royal Academy of Art, The Hague (KABK) residency. Her Himalayan Folk Collective archives oral traditions of the Western Himalayas, blending ethnography with digital preservation. Research emphasizes critical media literacy through AR/VR projects like Plastic Soup AR (2019) and Television Set Up Guide zine. Awards include KC Mahindra Scholarship (2022) and MIT Design X (2023).

• Climate Justice
• Decolonial Perspectives
• Environmental Studies
• +5 more

Jon Roozenbeek is an Affiliate Lecturer in the Department of Psychology at the University of Cambridge. His research focuses on the psychology of intergroup conflict, digital media effects, and countering misinformation. He has authored books including The Psychology of Misinformation and Propaganda and Ideology in the Russian-Ukrainian War , and lectures on Social Psychology and Advanced Topics in Social and Applied Psychology. His work examines authoritarianism, institutional trust, and the efficacy of inoculation interventions against misinformation. Key research themes include prebunking strategies, the impact of social media on polarization, and the role of identity in propaganda. Roozenbeek collaborates with the Cambridge Social Decision-Making Lab and actively contributes to global initiatives combating disinformation through gamified interventions and AI ethics research. His recent publications explore misinformation decay, AI's role in combating false narratives, and cross-cultural applications of prebunking. Roozenbeek’s work bridges academic research with practical solutions for digital misinformation challenges in education, public health, and international conflict contexts.

• Psychology of Misinformation
• Intergroup Conflict
• Digital Media Effects
• +5 more

Dr Aliaksandr Herasimenka is a political communication scholar at the Oxford Internet Institute, University of Oxford. As a Research Fellow with the Oxford Martin Programme on Misinformation, Science, and Media, he investigates how political groups and governments use AI and social media for campaigning and public opinion manipulation. His research examines: Digital propaganda and communication in authoritarian states Computational methods for tracking narrative circulation Organizational impacts of digital technologies on political campaigning Crisis-related misinformation during events like the Ukraine war Dr Herasimenka teaches social data science, journalism, and digital research methods across multiple institutions including University of Oxford and University of Westminster.

• Political Communication
• Computational Methods
• Digital Propaganda
• +2 more