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Olof SundinView profile

Professor

• Disinformation
• Generative AI
• Search Engines
• +5 more

Olof Sundin is Professor of Information Studies at Lund University's Department of Arts and Cultural Sciences, where he serves as Manager of Research and Research Education at the Division of ALM, Digital Cultures and Publishing Studies. He coordinates the research node Dīcit: Disinformation, Conspiracy Theories, and Infrastructures of Information. His research examines sociomaterial configurations and control mechanisms of digital information, focusing on: Disinformation dynamics and generative AI's impact on expertise/trust Search engine functionality in everyday contexts Media/information literacy as infrastructural meaning-making Evolution of information-seeking behaviors in AI-driven environments Recent publications demonstrate strong focus on AI's transformative impact on information literacy practices, source evaluation frameworks, and emerging digital market behaviors. His work consistently intersects technology, society, and epistemological concerns. Awards include: Best paper award (2025) Källkritikpriset: The golden magnifying glass 2023 (National award from Swedish Internet Foundation) Sundin leads multiple research initiatives: RE-SEARCH project (Swedish Research Council): Analyzing youth information-seeking in AI-infused educational environments 'Who is the Expert?' project (Crafoord Foundation): Investigating generative AI's impact on expertise and evidence Lund lead for 'The Digital Welfare State' project Member of Nordic Disinformation Resilience Network He coordinates the Dīcit research node and leads doctoral education in Information Studies, teaching courses on digital libraries and information institutions.

Sainyam GalhotraView profile

Assistant Professor

• Databases
• Data Management
• Responsible Data Science
• +7 more

Sainyam Galhotra is an Assistant Professor in the Department of Computer Science at Cornell University. His research focuses on developing data science tools for effective and responsible analytics, leveraging techniques from causal inference, data management, theoretical computer science, machine learning, and human-computer interaction to address challenges in trustworthy system design including robustness, explainability, and fairness. Education: Postdoc: University of Chicago PhD: University of Massachusetts Amherst (supervised by Barna Saha) BTech: Indian Institute of Technology Delhi (IIT Delhi) (supervised by Prof. Amitabha Bagchi) Research Interests: Dr. Galhotra's research spans several interconnected areas in data science and artificial intelligence. His work primarily focuses on Responsible Data Science , where he develops methods to ensure that data-driven systems operate fairly and transparently. Within this broad area, his specific interests include: Causal Inference techniques for understanding cause-effect relationships in complex data Algorithmic Fairness approaches to mitigate bias in machine learning systems Explainable AI methods that make black-box models more interpretable Data Management systems for efficient and reliable data processing Entity Resolution techniques for integrating data from multiple sources Trustworthy System Design that addresses robustness, explainability, and fairness His recent publications demonstrate a clear trend toward developing frameworks that combine causal reasoning with practical data management systems, particularly focusing on how to make data-driven decisions more transparent and equitable. The intersection of database systems with fairness considerations appears to be a particularly active area of his research. Scientific Awards: Rising Star in Data Science at the Data Science Institute, UChicago (Oct 2021) Computing Innovation Fellowship Award Recipient (by CRA, CCC and NSF) (Apr 2021) DAAD AInet Fellow (Feb 2021) ACM SIGMOD Entity Resolution Programming Contest – Top 5 finalist (May 2020) Most reproducible paper award in SIGMOD 2018 and 2019 (Jun 2019) First recipient of Krithi Ramamritham Computer Science Scholarship (Jun 2019) Best paper award in SIGSOFT FSE 2017 (May 2017) Dr. Galhotra is actively seeking students to collaborate with on his research projects. His work has been supported by various fellowships and awards, including the prestigious Computing Innovation Fellowship. He has mentored several students through his research projects, with a focus on developing the next generation of data scientists who can build responsible and trustworthy systems. His research group appears to focus on the intersection of database systems and responsible AI, developing tools like HypeR for causal reasoning, Ver for view discovery, and Nexus for correlation discovery in spatio-temporal data. This work suggests a cohesive research agenda centered around making data systems more transparent, fair, and user-friendly.

• Machine Learning
• Pattern Recognition
• Classification
• +6 more

Christian Igel is a Professor at the Department of Computer Science, University of Copenhagen, and serves as director of the SCIENCE AI Centre . He is also a co-lead of the Pioneer Centre for Artificial Intelligence in Denmark. His academic journey includes a Doctoral degree from Bielefeld University (2002) and a Habilitation degree from Ruhr-University Bochum (2010). Igel is a Juniorprofessor (2002–2010) and has held editorial roles at journals like KI - Künstliche Intelligenz and Artificial Intelligence Journal . Doctoral degree: Faculty of Technology, Bielefeld University, Germany (2002) Habilitation degree: Department of Electrical Engineering and Information Sciences, Ruhr-University Bochum, Germany (2010) His research spans Machine Learning , focusing on Support Vector Machines , Evolution Strategies , Reinforcement Learning , Deep Neural Networks , and PAC-Bayesian Analysis . He applies these methods to Environmental Monitoring , Medical Diagnostics , and Climate Research . Recent publications highlight work on adversarial machine learning , environmentally sustainable AI , and tree resource mapping using deep learning. His scientific awards include being a ELLIS Fellow . Igel’s software tools like Shark , woody , and Multi-Planar UNet are widely used in research and industry. Notable grants and collaborations involve projects with European Lab for Learning and Intelligent Systems (ELLIS) , SCIENCE AI Centre , and international teams in Denmark , Germany , and France . His lab leadership emphasizes open-source frameworks and reproducible research. Editorial Roles: German Journal on Artificial Intelligence , Evolutionary Computation Journal , Artificial Intelligence Journal Software Projects: Shark , woody , Multi-Planar UNet , U-Time Collaborations: SCIENCE AI Centre , Pioneer Centre for Artificial Intelligence , European Lab for Learning and Intelligent Systems

Jamie MorgensternView profile

Associate Professor

• Machine Learning
• Ethics & Fairness
• Human-Centered AI
• +3 more

Jamie Morgenstern is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering , University of Washington . She was previously an assistant professor at Georgia Tech and a Warren Center Fellow at University of Pennsylvania . Expertise: Ethics & Fairness, Human-Centered AI, Machine Learning Education: PhD in Computer Science from Carnegie Mellon University (2015) Her research examines the social impact of machine learning and ensuring ML models do not exacerbate societal inequalities. She investigates robustness to human-generated training data, fairness in clustering and active learning, and algorithmic equity in recommendation systems. Recent publications focus on interactive ML systems , fairness constraints , and privacy-preserving methods across conferences like NeurIPS, ICML, and AIES. Key subfields include multimodal learning , membership inference attacks , and data equity . Scientific Awards: NSF Career award for "Strategic and Equity Considerations in ML" Simons collaboration project Simons Award for Graduate Students in Theoretical Computer Science (2014-2016) NSF GFRP fellowship Microsoft Research Graduate Women's Scholarship Spotlight presentation at NeurIPS 2015 Mentoring: She advises current PhD students Rachel Hong , Jie (Claire) Zhang , and Yuanyuan (Chloe) Yang . Former advisees include Daniel Jiang (MS), Bhuvesh Kumar (PhD), and Angel (Alex) Cabrera (BS). Grants: Funded by NSF Career award and Simons collaboration projects. Previously supported by Simons, NSF, and Microsoft Research fellowships. Labs & Collaborations: Collaborates with researchers like Michael Kearns , Aaron Roth , and Avrim Blum . Affiliated with the Allen School's Artificial Intelligence research group.

Seth FreyView profile

Associate Professor

• Computational Social Science
• Governance of Commons
• Complex Systems
• +5 more

Seth Frey is an Associate Professor in the Department of Communication at the University of California, Davis, with affiliate status at Indiana University's Ostrom Workshop and as Research Director at Metagov. His research focuses on computational social science approaches to understanding self-governance in complex social systems, particularly through the lens of online communities as model institutions. Education: Ph.D. in Cognitive Science and Informatics (complex systems), Indiana University, 2013 B.A. in Cognitive Science, UC Berkeley, 2004 Research Interests: Frey specializes in computational approaches to institutional analysis and the cognitive science of strategic behavior . His work examines how communities design governance systems to overcome collective action problems, with emphasis on: Emergent institutional structures in digital commons Policy-as-data through NLP and institutional grammar frameworks Cognitive mechanisms underlying cooperative behavior Design principles for participatory change in online platforms His methodology integrates large-scale data analysis, web-based experiments, and computational modeling across diverse contexts including Minecraft, Reddit, and professional sports ecosystems. Publication Trends: Recent publications (2023-2025) demonstrate a cohesive trajectory toward computational institutional analysis, with increasing focus on NLP-driven policy analysis (e.g., NLP4Gov), decentralized governance architectures (DAOs, multi-level platform governance), and the cognitive foundations of collective action. His work consistently bridges theoretical institutional analysis with practical applications in digital community design, showing particular growth in translating Ostrom's design principles into computational frameworks. Awards: Honorable Mention Award for Best Paper at ACM CSCW 2019 Advising and Grants: Frey mentors students interested in data science applications at the intersection of communication, cognition, and complex systems, emphasizing resourcefulness and intellectual curiosity. His research has secured substantial funding from: National Science Foundation (NSF) NASA Ford Foundation Google Open Source Foundation He actively encourages aspiring graduate students with strong self-directed research skills to explore computational approaches to social phenomena. Labs and Teams: He leads the Computational Communication Lab at UC Davis and co-directs the Institutional Grammar Research Initiative. Through Metagov, he develops the 'Governance API' framework for modular community governance. His past affiliations include Disney Research (Walt Disney Imagineering) where he applied complexity science to theme park systems, and the New England Complex Systems Institute (NECSI). Current collaborations span Ethereum governance, Minecraft server ecosystems, and Colorado's cannabis monitoring infrastructure.

Audrey BowdenView profile

Associate Professor

• Biomedical Optics
• Point-of-Care Diagnostics
• Biomedical Imaging
• +4 more

Audrey Bowden is an Associate Professor at Vanderbilt University in both the Department of Biomedical Engineering and Department of Electrical and Computer Engineering . She is also the Dorothy J Wingfield Phillips Chancellor Faculty Fellow . Education: PhD in Biomedical Engineering (2007) from Duke University BSE in Electrical Engineering (2001) from Princeton University Research Interests: Bowden's work focuses on biomedical optics and point-of-care diagnostics , with a strong emphasis on addressing healthcare disparities through low-cost technologies. Key areas include: Biomedical Imaging Biophotonics Image Processing Machine Learning in Medical Imaging Optical Coherence Tomography (OCT) Functional Near-Infrared Spectroscopy (fNIRS) Publication Trends: Recent work combines machine learning with endoscopic imaging to differentiate cancer from inflammation, develops low-cost OCT systems for smartphones, and improves fNIRS accessibility for diverse patient populations. Her lab also focuses on 3D reconstruction algorithms for urological applications and specular reflection removal in endoscopic videos. Lab & Clinical Collaborations: The Bowden Biomedical Optics Laboratory (BBOL) collaborates with clinical departments including urology , dermatology , otolaryngology , and women's health . The lab integrates optics , microfluidics , and computer science to create hardware/software tools for resource-constrained environments.

Murat KantarciogluView profile

Professor

• Data Security
• Artificial Intelligence Security
• Privacy-Preserving Technologies
• +5 more

Murat Kantarcioglu is a Professor of Computer Science at Virginia Tech, affiliated with the College of Engineering. He is also a Faculty Fellow at the Commonwealth Cyber Initiative (CCI) and directs the Data Security and Privacy Lab. Previously, he held the Ashbel Smith Professorship at the University of Texas at Dallas. His research focuses on data and AI security, privacy, blockchain, and cybersecurity. He has received notable awards, including the NSF CAREER Award and IEEE Technical Achievement Award, and is a Fellow of AAAS and IEEE. Education: Ph.D. in Computer Science (Purdue University), B.S. in Computer Engineering (Middle East Technical University). Research Interests: Privacy-preserving machine learning and data analytics Adversarial machine learning and cybersecurity Blockchain technology and applications Healthcare data security and genomics privacy Risk and incentive models for assured data sharing Awards and Recognition: NSF CAREER Award AMIA Homer R. Warner Award IEEE ISI Technical Achievement Award Fellow of AAAS and IEEE Distinguished Member of ACM Advising and Labs: Directed over 20 PhD/Master’s students, many in cybersecurity and privacy domains. Founder and director of Virginia Tech’s Data Security and Privacy Lab. Associate at Harvard’s University Data Privacy Lab. Service and Leadership: Extensive program committee roles in top conferences (KDD, AAAI, IEEE ICDE). Former CCI co-chair for IEEE TrustCom. Co-authored influential textbooks on adversarial machine learning.

Yujie ChenView profile

Associate Professor

• Digital Media
• Digital Labour Studies
• Platform Studies
• +3 more

Dr. Yujie (Julie) Chen is an Associate Professor (on leave) at the University of Toronto's Faculty of Information, affiliated with the Department of Communication, Culture, Information & Technology (CCIT). Her work focuses on digital media's political economy, platform capitalism, and digital labour studies. She authored Super-Sticky WeChat and Chinese Society , analyzing WeChat's societal integration and platform power dynamics in China. Her research critiques how labour is marginalized in datafication discourse, particularly in platform-mediated sectors like ride-hailing (DiDi) and food delivery. Key themes include algorithmic control, worker resistance, and the interplay between technology, state policies, and labour conditions in China. Dr. Chen’s work bridges sociotechnical systems analysis with critical political economy frameworks. Her recent studies explore temporal exploitation in platform labour (e.g., food delivery workers’ time management), gamification of work processes, and the 'digital utility' concept deployed by platforms to justify market dominance. She frequently presents at conferences like AoIR and ICA, emphasizing global platform capitalism’s socio-economic impacts. Dr. Chen is completing a book manuscript examining labour’s erasure in datafication narratives and advocating for analytical frameworks that foreground embodied labour experiences. Her research also intersects with global South labour comparisons, notably between China and the Philippines in platform economies.

Olga GoriunovaView profile

Professor

• Cultural Theory
• Digital Humanities
• Media Philosophy
• +5 more

Olga Goriunova is a Professor in the Department of Media Arts at Royal Holloway, University of London, and affiliated with the Humanities and Arts Research Institute. She holds a PhD in Digital Media from Aalto University and a philology degree from Lomonosov State University. Her research spans cultural theory, media philosophy, and AI ethics, focusing on how technology reshapes subjectivity and ecology. Research interests include digital art practices, data abstraction in AI, and the intersections of ecology with technical systems. Notable works include *Bleak Joys* (2019) and the upcoming *Ideal Subjects* (2025). She co-founded the journal *Computational Culture* and led projects like StoryFutures Academy funded by UKRI. Recent collaborations span global institutions including ANU and Leuphana University’s Digital Cultures Lab. She has served on AHRC peer review panels and edited volumes on software studies. Current roles include Director of Research for Media Arts and REF lead.

Devansh SaxenaView profile

Assistant Professor

• Responsible AI
• Human-AI Interaction
• Public Interest Technology
• +3 more

Devansh Saxena is an Assistant Professor at the University of Wisconsin-Madison, holding dual affiliations in the Information School and the School of Computer, Data & Information Sciences. His research focuses on sociotechnical practices of decision-making in high-stakes domains, particularly examining the social impacts of AI in government agencies, community-based organizations, and public health. Saxena employs mixed-methods approaches, blending computational and design methods to develop human-centered AI systems that prioritize equity and collective decision-making. He holds a Ph.D. in Computer Science from Marquette University, advised by Dr. Shion Guha and Dr. Michael Zimmer. His work intersects Human-Computer Interaction (HCI), Machine Learning, and FAccT (Fairness, Accountability, and Transparency in Sociotechnical Systems). Key areas of research include responsible AI, participatory algorithm design, and rethinking risk assessment in public sector systems such as child welfare. Saxena has received prestigious recognition, including the Best Paper Award at CHI 2023 and the Presidential Postdoctoral Fellowship at Carnegie Mellon University. Recent projects include analyzing algorithmic harms in child welfare through casenote computational analysis, advocating for participatory AI frameworks in government, and exploring ethical AI innovation in early-stage concept selection. His work emphasizes bridging technical and sociocultural dimensions to ensure technologies serve public interest.

• Immersive systems (VR, AR, MR, XR)
• Human-AI interaction and intelligent user interfaces
• HCI theory and methodology
• +3 more

Professor Eduardo Velloso is an academic staff member at the School of Computer Science , University of Sydney . He is a member of the Centre for AI Trust and Governance and holds a PhD in Computer Science from Lancaster University and a Bachelor of Computer Engineering from Pontifical Catholic University of Rio de Janeiro. Teaches COMP4447/5047 - Pervasive Computing and INFO1111 - Computing Professionalism Research Interests focus on distributed collaboration in mixed reality , human-AI interaction , and HCI theory and methodology . His work integrates Engineering, Design, and Psychology to explore gaze interaction, adaptive agents, and multimodal interfaces. Key projects include Blended Whiteboard for remote MR collaboration and GazeGrip for mobile accessibility. Publication Trends show expertise in Virtual Reality , Mixed Reality , and Human-AI Interaction , with recent work on Algorithmic Recourse and Immersive Educational Tools . Awards include ACM Best Paper Awards at CHI, UIST, TOCHI, and DIS venues. Scientific Awards 2024 ACM CHI & DIS Honorable Mentions 2022 UoM-FEIT Teaching & Learning Award 2019 UoM-CIS Excellence in Research Award 2015 ACM UIST Best Paper Award Advising includes supervision of research students Marvin, Tinghui LI, and Wendi YU in projects on asynchronous MR collaboration , situationally-induced impairments , and physical environment integration . His lab explores AI-assisted interaction and context-aware computing through projects like SpinalLog and LiftSmart .

Yizhou SunView profile

Professor

• Machine Learning
• Artificial Intelligence
• Graph Neural Networks
• +3 more

Professor Yizhou Sun is affiliated with the University of California Los Angeles (UCLA) and the Henry Samueli School of Engineering and Applied Science . Her academic work focuses on Machine Learning , Artificial Intelligence , and Graph Neural Networks within the Computer Science department. Her research spans High-Level Synthesis , Causal Inference , and Computational Biology , with recent publications addressing neural network compression, language model safety, and dynamical system modeling. The trends in her recent 2025 and 2024 publications emphasize Deep Learning , Graph Theory , and Language Model Optimization , reflecting interdisciplinary applications in Biomedical Data , Hardware Design , and Physical Simulation .

Jonathon HutchinsonView profile

Associate Professor

• Social Media Studies
• Public Service Media
• Cultural Intermediation
• +4 more

Introduction Jonathon Hutchinson is an Associate Professor and Chair of the Media and Communications Discipline at the University of Sydney. He holds roles as Editor-in-Chief of the Policy & Internet journal and Chief Investigator on major projects like the International Digital Policy Observatory (ARC LIEF) and the eSafety Commission's Emerging Online Safety Issues initiative. His work bridges digital media studies, policy analysis, and cultural theory. Education BComm (Hons), RMIT University PhD, ARC Center of Excellence for Creative Industries and Innovation, QUT Research Interests Hutchinson focuses on digital intermediation processes in cultural production, algorithmic governance, and public service media adaptation. Key areas include: Algorithmic influence on news diversity Social media policy and youth safety Platform politics and regulatory frameworks Recent Article Trends His 2020–2025 work emphasizes global digital policy challenges, generative AI ethics, and Vietnamese media dynamics. Recent projects highlight cross-national comparisons (e.g., China/South Korea news ecosystems) and participatory co-design approaches to online safety education. Awards & Grants 2023 ARC LIEF Grant 2021 eSafety Online Safety Grant Multiple industry partnerships (e.g., eSafety Commissioner, Hans-Bredow-Institut) Advising & Grants Supervised over 15+ graduate students (PhD/Master's/Honours) in media studies and digital culture. Active in interdisciplinary grants addressing cybersecurity, AI governance, and platform regulation. Labs & Networks Member of the Sydney Centre for Healthy Societies, Sydney Southeast Asia Centre, and Charles Perkins Centre. Leads the International Digital Policy Observatory project tracking global regulatory trends.

Thierry WarinView profile

Professor

• Data Science for Global Transformations
• Platform Economy
• Industrial Organization
• +7 more

Thierry Warin is a Full Professor of Data Science for International Business at HEC Montréal, directing the Department of International Business. He holds the Professorship in Data Science for International Business and is a Principal Investigator at CIRANO, leading the World Economy theme. His roles include affiliations with Harvard Business School’s Microeconomics of Competitiveness program and the International Trade and Finance Association presidency (2020-2022). Education: PhD from ESSEC Business School (France, 2000). Professional development includes the Harvard Business Analytics Program (2018-2020) and GIS training at Harvard. Research Interests: Data science applications in global economic transformations, including network theory, natural language processing, and computational methods. Focus areas: algorithmic collusion, platform economies, and metadata-driven analyses. He develops open-source tools like the statcanR package and advocates for reproducible research. Articles Trends: Recent work explores AI regulation, algorithmic competition, climate transition plans, and central bank speech analysis. Methodologies span structural topic modeling, social media analytics, and entropy-based frameworks. Awards: Honored with the Highly Commended Paper Award (2017-2018) and Emerald Literati Award (2018) for reverse innovation research. Recognized for contributions to computational social science and regulatory frameworks. Advising & Grants: Supervised 16 master’s projects since 2019, focusing on data science applications in global business challenges. Active in interdisciplinary initiatives like the St. Lawrence–Great Lakes corridor data hub. Labs & Philanthropy: Founded quantum simulations and leads Ed’Haîti , an NGO addressing education in Haiti. Collaborates on Science des données au féminin en Afrique , empowering 200 African women with data science skills.

Didar ZowghiView profile

Researcher

• Artificial Intelligence Ethics
• Data Quality Management
• Requirements Engineering
• +4 more

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.