Ashton Anderson is an Associate Professor in the Department of Computer Science at the University of Toronto's Faculty of Arts & Science, where he leads the Computational Social Science Lab. His work intersects AI, data science, and societal impact, examining topics from algorithmic fairness to online behavior. Research investigates human-AI collaboration , social media dynamics , and computational ethics . Recent projects evaluate LLMs' impact on creativity and social media's agenda-setting power. His group develops methods to audit algorithmic systems for bias and alignment. Honored with a Google PhD Fellowship and NSERC Scholarship, he mentors graduate students in social computing and human-centered AI. His teaching covers social network analysis and computational social science methodologies.
Dr. Koustuv Saha is an Assistant Professor of Computer Science at the University of Illinois Urbana-Champaign (UIUC), leading the OnCARE lab. He holds a PhD from Georgia Tech and a B.Tech from IIT Kharagpur. His research focuses on computational social science, social computing, and ethical AI applications in mental health and wellbeing. His work bridges computer science with psychology, sociology, and public policy to address societal challenges. Education: PhD in Computer Science (Georgia Tech, 2021), B.Tech in CSE (IIT Kharagpur, 2012). Previous roles include Senior Researcher at Microsoft Research Montreal (FATE group) and industry research experience in Silicon Valley. Research interests include wellbeing sensing technologies, algorithmic fairness, and large language models’ societal impacts. Recent work examines caregiver mental health, deceptive wellness apps, and AI ethics in content moderation. His studies combine causal inference, NLP, and multimodal data analysis. Publications span top venues like CHI, CSCW, ICWSM, and JMIR. Notable awards include Georgia Tech’s Outstanding Dissertation Award (2022) and Snap Research Fellowship (2020). He advises on AI governance and collaborates with policymakers, clinicians, and industry. OnCARE lab explores human-centered AI for societal good, with projects on mental health support systems, ethical tech design, and algorithmic transparency in health contexts. Current focus includes caregiver AI tools, LLM-based empathetic systems, and workplace wellbeing interventions.
Professor Ian Ruthven is a Professor of Information Seeking and Retrieval in the Department of Computer and Information Sciences at the University of Strathclyde. He chairs the Scottish Library and Information Council (SLIC) and the Steering Committee of the Information Seeking in Context (ISIC) conference series. His research focuses on human information interaction, including information seeking in health, migration, and cultural heritage contexts. He authored Dealing With Change Through Information Sculpting , proposing a theory explaining how people use information behaviors to adapt during life transitions. Education: PhD in Abduction, Explanation, and Relevance Feedback (University of Glasgow, 2001), MSc (University of Birmingham, 1993), BSc in Computing Science (University of Glasgow, 1992). Research Interests: Information seeking theory, interface design for information access, user studies. His work bridges human-computer interaction with socio-technical systems, emphasizing ethical and inclusive design. Publications: Over 170 peer-reviewed papers, including influential works on information resilience, digital divides, and pandemic impacts on international students. Recent work includes Grey Digital Divide: Factors Associated with Older People’s Use of the Internet for Financial Transactions (2025) and Information Avoidance: A Critical Conceptual Review (2025). Awards: Tony Kent Strix Memorial Award (2020), Fellow of the Royal Society of Arts (2010), and multiple best paper awards. His contributions span academic and policy realms, addressing societal challenges through information science. Projects: Co-investigator in the Participatory Harm Auditing Workbenches and Methodologies (PHAWM) project (2024–2028) and leader of the Scottish Network on Digital Cultural Resources Evaluation (ScotDigiCH) (2015–2016). These projects emphasize participatory design and cultural heritage evaluation. Professional Activities: Editorial roles for major conferences, visiting researcher at the University of Pretoria (2021), and advisory roles in library and information science initiatives. His work fosters collaboration between academia and cultural institutions.
Onur Varol is an Assistant Professor at Sabanci University's Computer Science Department and leads the VIRAL Lab, which focuses on computational social science, network science, and machine learning. He has affiliations with the Center of Excellence for Data Analytics. His research spans social bot detection, misinformation analysis, and online behavior modeling.
Ke Yang serves as Assistant Professor in the Department of Computer Science at the University of Texas at San Antonio (UTSA), College of Sciences. He founded and leads the Cohort for AI REsponsibility (CAREAI) initiative, while also holding core faculty positions in UTSA's School of Data Science and MATRIX (AI Consortium for Human Well-being). Education: Ph.D. from New York University (supervised by Prof. Julia Stoyanovich) Research Focus: Dr. Yang's work centers on AI trustworthiness and responsibility , with specialized expertise in algorithmic fairness, data ethics, and human-centered data science. His research addresses critical challenges including Large Language Model hallucinations, explainable AI frameworks, and algorithmic accountability mechanisms. He actively develops open-source tools like Ranking Facts and FairDAGs to implement these principles in practical systems. Publication Trends: Recent work (2020-2025) demonstrates evolving focus from foundational fairness in ranking systems toward generative AI safety and medical applications. His publications show strong theoretical grounding combined with real-world implementation, particularly in privacy policy analysis and medical question-answering systems using causal inference techniques. Scientific Recognition: Pearl Brownstein Doctoral Research Award (NYU Tandon School of Engineering) CDS Postdoctoral Fellowship (University of Massachusetts) Professional Development: Dr. Yang has secured significant research funding including the CDS Postdoctoral Fellowship at UMass. His graduate work at NYU and Drexel University was fully supported by research assistantships, demonstrating consistent funding acquisition throughout his career. He actively contributes to academic community building through conference tutorials and educational initiatives. Research Ecosystem: He directs CAREAI at UTSA while collaborating across institutional boundaries through MATRIX and the School of Data Science. Previously, he contributed to the Data systems Research for Exploration, Analytics, and Modeling (DREAM) lab and Center for Data Science at UMass Amherst, maintaining continuity in his responsible AI research trajectory.
Param Vir Singh is the Carnegie Bosch Professor of Business Technologies and Marketing and Associate Dean for Research at Carnegie Mellon University’s Tepper School of Business. His research examines how AI and algorithmic systems reshape markets, influence consumer trust, and redefine platform strategy, pricing, and fairness. He leads the Collaborative AI Initiative at CMU, focusing on adaptive learning environments for business education. Affiliations : Carnegie Mellon University, Tepper School of Business Editorial Roles : Senior Editor at Information Systems Research , Associate Editor at Management Science Research Themes : AI ethics, algorithmic fairness, platform economics, consumer behavior, and generative AI applications. Key Research Contributions : His work spans algorithmic pricing, bias mitigation, sharing economy dynamics, and AI-driven inequality analysis. Articles often intersect computer science, economics, and marketing. Scientific Recognition : INFORMS Information Systems Society Distinguished Fellow Award Don Lehmann Award (Winner) John DC Little Award Don Morrison Long-Term Impact Award (Finalist) AIS Senior Scholar's Best Paper Award (Winner) Academic Leadership : Served as Director of the PNC Center for Financial Services Innovation, securing $5.5M for research programs. Mentored PhD students now at Harvard, NYU, Michigan, and other top institutions.
Dr. Corey B. Jackson is an Assistant Professor in The Information School at the University of Wisconsin–Madison, affiliated with the Robert & Jean Holtz Center for Science and Technology Studies, Institute for Diversity Science, and Data Science Institute. His research bridges human-centered computing, CSCW, and design epistemologies, focusing on socio-technical systems for equitable participation in AI and citizen science. He teaches courses in Interaction Design, User Experience, and Digital Information. Education: Ph.D. Library & Information Science, Syracuse University, 2019 M.S. Library & Information Science, University of Illinois, Urbana-Champaign, 2012 B.A. Political Science, University of Illinois, Urbana-Champaign, 2010 Research Interests: Jackson’s work emphasizes designing systems for transparency, accountability, and democratic participation in technologies. He explores AI fairness, citizen science, and civic technology. His methodologies include mixed methods and socio-technical analysis. Key Awards: ACM CSCW 2020 Honorable Mention (Best Paper) NSF HCC Grant (2021–2024) Rockefeller Foundation Grant (2021) Chan Zuckerberg Initiative Grant (2022–2023) Advising & Grants: Jackson mentors Ph.D. students in HCI and citizen science. His grants total over $612k, supporting projects like AI audit tools and environmental justice initiatives. He co-directs the Collaborative Computing Group. Labs & Teams: Collaborative Computing Group at UW-Madison; affiliated with interdisciplinary institutes advancing data science and diversity in science.
Didar Zowghi is a Senior Principal Research Scientist and Science Team Leader at CSIRO Data61, Australia's national science agency. His work focuses on advancing ethical AI systems, data quality frameworks, and requirements engineering methodologies. He leads research initiatives addressing challenges in AI governance, diversity/inclusion in technology, and human-centered AI development. Research interests include AI ethics, data completeness in healthcare systems, and the application of machine learning in requirements engineering. His contributions span theoretical frameworks for responsible AI patterns, empirical studies on user perceptions of AI tools like M365 Copilot, and analysis of AI's role in global diplomatic practices. Zowghi has published extensively on topics ranging from blockchain in supply chains to pedagogical innovations in software engineering education. His work often bridges technical systems and societal impacts, emphasizing real-world implementation challenges through collaborative industry-academia projects. Notable outputs include the Responsible AI Pattern Catalogue and studies examining barriers to data quality in IoT platforms. He has pioneered frameworks linking innovation initiatives to occupational skill requirements and developed tools like Elica for dynamic requirements knowledge extraction in agile teams.
Professor Catherine Easton serves as Professor in Information Technology and Intellectual Property Law at Lancaster University's School of Law, with additional affiliations at Security Lancaster and the Centre for Law and Society. Her work bridges legal scholarship with practical technology implementation, focusing on digital inclusion and governance frameworks. Her research centers on internet governance, domain name regulation, intellectual property law, and accessibility for disabled users. She examines how legal frameworks interact with human-computer interaction systems, particularly in crisis response scenarios and educational technology. Her scholarship consistently addresses the tension between regulatory compliance and genuine digital inclusion, with special attention to the UN Convention on the Rights of Persons with Disabilities. Her recent publications reveal growing emphasis on autonomous systems regulation, particularly regarding disability access in driverless vehicles, and ethical frameworks for cloud-based disaster response. The scholarly trajectory shows evolution from foundational website accessibility analysis toward complex systems governance in emerging technologies. Higher Education Academy International Scholarship recipient MMU Promising Researcher Fellow (2011) Co-chair of UN Internet Governance Forum's Internet Rights and Principles Dynamic Coalition Treasurer of British and Irish Law, Education and Technology Association Guest editor for Web Journal of Current Legal Issues Disability Special Edition Professor Easton actively develops legal education technologies, having created interactive teaching resources for major textbooks and pioneered clicker technology applications in law classrooms. She leads initiatives like the National Law Student Forum and has presented extensively on MOOCs and legal pedagogy. Her Security Lancaster affiliation connects her work to broader research on information transparency and crisis response ethics, where she examines big data's implications for inclusion and human rights.
Dr. Reuben Binns is an Associate Professor of Human Centred Computing at the University of Oxford , where he investigates intersections between computer science, law, and philosophy. His research focuses on data protection , machine learning ethics , and regulation of technology .
Dr. Asieh Hosseini Tabaghdehi is a Senior Lecturer in Strategy & Business Economy at Brunel Business School, Brunel University of London. She serves as Programme Lead for the BSc International Business Programme and Trade2Grow Executive Education Programme. Additionally, she is Impact Lead at the Brunel Centre for AI: Social and Digital Innovation, where she leads the capability area in the Future of Work. Dr. Tabaghdehi is also an economist and social impact advisor for the independent NGO, Social Innovation Movement. Dr. Tabaghdehi earned her PhD in Economics and Finance (2008) and MSc in International Money, Finance, and Investment (2015), both from Brunel University London. She also holds a BA in Theoretical Economics from University of Mazandaran. She completed the Postgraduate Certificate in Academic Practice and is a Fellow of the Higher Education Academy. Dr. Tabaghdehi is internationally recognized for her research on digital transformation, with particular expertise in the ethical integration of artificial intelligence and digital technologies. Her work focuses on how emerging technologies shape industries, labor markets, and society, with emphasis on enhancing SME growth through technological innovation. She explores applications across critical sectors including social care, supply chain management, and environmental sustainability. A central theme in her research is smart data governance, ensuring ethical, transparent, and responsible use of data in decision-making processes. Her research portfolio demonstrates a consistent focus on the intersection of technology, ethics, and business strategy. She has developed frameworks like the Digital Business Auditing Framework, which has been adopted internationally for smart city initiatives. Her work connects academic research with practical policy applications, as evidenced by her presentations as oral and written evidence to the House of Commons Select Committee. Her publications span AI ethics, digital footprint implications, fertility economics, and healthcare cost analysis, showing interdisciplinary breadth while maintaining thematic coherence around digital transformation's societal impact. Scientific Awards and Recognition Semi-finalist: Research Impact Award at Brunel University London, 2023 Staff Award: Exceptional in Collegiality and Supportive to Colleagues at Brunel University London, 2022 Exceptional Performance at Regents University London, 2018-19 Staff Award in Teaching, Learning and Assessment at Regents University London, 2016 Best Lecturer Award at London Brunel International College, 2014 Best Lecturer Award at London Brunel International College, 2013 Dr. Tabaghdehi actively supervises PhD students researching areas including Smart Data Governance, Ethical AI Governance, Digital Innovation Impact, Responsible AI Adoption Strategies, Sustainability, and Future of Labour Market. She has secured research funding from multiple sources including the Economic & Social Research Council (ESRC), Brunel University London, and Brunel Business School. Her current projects include research on AI Adoption and Governance, Youth digital addiction, Algorithm Reliability Framework, and SMEs digital footprints. She has also co-designed the "Digital Adoption" module for the UK Government's Help to Grow Management program, demonstrating the practical application of her research. As a member of multiple professional organizations, Dr. Tabaghdehi serves as an associate practitioner at Social Value International, associate member of the Big Innovation Centre, and member of the All-Party Parliamentary Group on AI. She is also a member of the ESRC Review College, British Academy of Management Review College, and Energy Institute UK, contributing to the broader academic and policy communities through these roles.
Danaë Metaxa is an Assistant Professor at the University of Pennsylvania, with a primary appointment in the Department of Computer and Information Science and a secondary appointment at the Annenberg School for Communication. They co-founded the Penn HCI group and focus on bias and representation in sociotechnical systems, particularly in high-stakes domains like politics and employment. Primary: Department of Computer and Information Science, University of Pennsylvania Secondary: Annenberg School for Communication Their research develops sociotechnical auditing methods that combine algorithmic analysis with user-centered behavioral interventions. Key areas include algorithmic justice, human-computer interaction, and marginalized groups' experiences with AI systems. Recent publications analyze generative AI harms, political content on TikTok, and automated hiring biases. They emphasize youth participation in algorithm auditing and ethical AI education. Danaë teaches courses like Algorithmic Justice and Human-Computer Interaction , and mentors PhD students in interdisciplinary research. They are a General Chair for FAccT 2025 and advocate for equity in AI research opportunities.
Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data
Kevin Baum is a computer scientist currently serving as the deputy head of the Neuro-Mechanistic Modelling (NMM) department at the German Research Center for Artificial Intelligence (DFKI) since January 2023, and head of the Centre for European Research in Trusted AI (CERTAIN) at DFKI since December 2023. Based at the Saarland Informatics Campus in Saarbrücken, Germany, he completed his doctorate in philosophy in March 2024, combining technical expertise with philosophical depth. His work bridges computer science with ethics, focusing on making AI systems transparent and accountable to human users. Dr. Baum's research program centers on interdisciplinary questions concerning the explainability and transparency of AI systems. His work spans multiple significant projects including the Explainable Intelligent System (EIS) initiative and project E7 of the Transregional Collaborative Research Centre 248 "Foundations of Perspicuous Software Systems" (CPEC). He has developed frameworks for understanding stakeholder perspectives on explainable AI and investigated how different information types about automated systems affect user perceptions of fairness and justice. His approach consistently combines theoretical foundations with practical implementations across diverse contexts. Analysis of his publication trends reveals a clear trajectory from theoretical foundations in machine ethics toward practical implementations of explainability requirements in real-world contexts. His work demonstrates increasing focus on human oversight effectiveness, fairness monitoring, and ethical considerations across various AI applications. He has made significant contributions to both academic discourse and practical AI development guidelines, with publications spanning computer science, philosophy, psychology, and human-computer interaction venues. Award for Ethics for Nerds lecture series As a research leader, Dr. Baum contributes to shaping AI development practices through his departmental leadership and interdisciplinary collaborations. His current work with CERTAIN focuses on establishing European research standards for trusted AI development and deployment, emphasizing the practical implementation of ethical requirements in AI systems. He maintains active collaborations across multiple institutions and disciplines, reflecting his commitment to bridging technical and philosophical considerations in AI development. At DFKI, he leads research that combines neuroscientific insights with AI development to create more interpretable systems. The NMM department focuses on both theoretical research on explainable AI foundations and practical applications in various domains, with particular attention to how different stakeholders understand and require explanations from AI systems.
Prof. Dr. Ben Wagner is a Professor of Media, Technology & Society at Inholland University, Director of TU Delft's AI Futures Lab on Rights and Justice, and Professor of Human Rights & Technology at IT:U. His work bridges social sciences, technology, and human rights, focusing on digital governance, AI ethics, and societal impacts of technological change. He holds a PhD from the European University Institute (2013) and has led institutions like the Center for Internet & Human Rights (Viadrina) and the Sustainable Computing Lab (WU Wien). Key initiatives include Inholland's Digital Rights Research Team (DRRT), Sustainable Media Lab (SML), and contributions to the European Cloud for Heritage OpEn Science (ECHOES). His research emphasizes designing accountable tech systems, digital rights frameworks, and sustainable digital infrastructures. Recent work addresses gaps between legal/ethical guidelines and public sector data practices, AI governance across nations, and audit mechanisms for platform transparency. Awards include the 2023 Best Paper Award at HICSS for AI governance research and a 2013 Best Student Paper at Internet Science. Collaborations span academia, governments, and industries to shape equitable tech policies. Active in advisory roles for ENISA, Patterns Journal, and the UKRI Trustworthy Systems Hub.
