Oana Goga is a Research Director at Inria, affiliated with the CEDAR team and Laboratoire d'Informatique de l'École Polytechnique (LIX). She holds a Ph.D. from Pierre et Marie Curie University. Her research focuses on AI and Society, addressing risks in online platforms, privacy, disinformation, and child protection. She leads interdisciplinary projects with economists, legal scholars, and social scientists. Awards & Grants: CNRS Bronze Medal (2024) Lovelace-Babbage Award (2023) ERC Starting Grant (2022) Andreas Pfitzmann Best Student Paper Award (2024) Advising & Tools: Guides Ph.D. students and postdocs on projects like CheckMyNews and AdAnalyst . Developed tools for auditing political ads and measuring platform risks. Labs & Collaborations: Active in the Inria CEDAR team and collaborates internationally on EU initiatives like the European Panel for Disinformation Monitoring .
Prof. Dr.-Ing. Christian Grimme is an Associate Professor and Extraordinary Professor in the Department of Information Systems at the University of Münster. He leads the Computational Social Science and Systems Analysis research group. His roles include acting professorships, research group leadership, and academic co-direction of the ERCIS Competence Center for Social Media Analytics. He holds a Dr.-Ing. in Computer Science and has extensive postdoctoral and habilitation experience. Education Timeline: 2015–2018: Habilitation and venia legendi in Information Systems 2006–2012: PhD in Computer Science (Dr.-Ing.) 1999–2006: Diploma in Computer Science Research Interests focus on Multiobjective Evolutionary Computation, Social Media Analysis, Disinformation Detection, and AI Ethics. His work bridges algorithmic innovation (e.g., optimization algorithms) with societal challenges (e.g., automated propaganda detection). Recent projects include analyzing Large Language Models' role in disinformation mitigation and real-time social media content analysis using human attention mechanisms. Awards include the Best Teaching Award (2024), PPSN XIV Best Paper Award (2016), and multiple travel grants from ACM and DAAD. He actively participates in conferences like GECCO and EMO, contributing to both theoretical and applied research. Advising and grants highlight his role in guiding over 20 theses, spanning Master's and Bachelor's projects in IS/WI. Notable grants include DAAD-funded collaborations and internal university funding for projects like MODERAT! (moderation tools) and ERCIS SMA Competence Center. Labs/Teams: Leads the Computational Social Science & Systems Analysis group, collaborating with global partners via ERCIS. Engages in initiatives like CLAIRE and the Integrity & Security Initiative to address AI ethics and information security challenges.
Arryn A. Guy is an Assistant Professor of Psychology at Illinois Institute of Technology, affiliated with the Lewis College of Science and Letters. She is core clinical faculty in the Clinical Psychology Ph.D. program and a research faculty member at the Center for Health Equity, Education, and Research (CHEER). Dr. Guy leads the CRAFT lab, focusing on community-based participatory research with queer and trans communities. Education: Postdoctoral Fellowship, T32 Biobehavioral HIV Research Training, Rhode Island Hospital, Brown University (2020–2022) Ph.D., Psychology (Clinical), Illinois Institute of Technology (2020) Predoctoral Clinical Internship, Edward Hines Jr. VA Hospital (2019–2020) M.S., Psychology, Illinois Institute of Technology (2017) B.A., Psychology (Philosophy minor), Arizona State University (2014) Dr. Guy's research focuses on healing psychological sequelae from stigma, supporting addiction recovery, increasing access to gender-affirming care, and reducing HIV health inequities. Her work integrates Community-Based Participatory Research (CBPR) , LGBTQ+ health , contextual behavioral science (ACT, Mindfulness) , and peer support . She examines the impacts of cisgenderism, racism, heterosexism, and substance use stigma on behavioral health outcomes. Her recent publications highlight trends in minority stress , mindfulness-based interventions , peer-led models , and HIV care integration with mental health and substance use services. Her work often involves mixed-methods designs and focuses on structural and interpersonal determinants of health among marginalized populations. Scientific Awards: Excellence in Teaching Award, Graduate Student category, Department of Psychology, Lewis College of Human Sciences, Illinois Institute of Technology, 2019 NIH Extramural Loan Repayment Award for Clinical Research (L30AA029578), NIAAA, 2021–2023 NIH Extramural Loan Repayment Award for Clinical Research (L30DA059347), NIDA, 2023–2025 Dr. Guy has been actively involved in advising and securing research funding. She served as MPI on a PCORI subaward and PI on an NIAAA-funded pilot. Currently, she is the PI of a NIDA-funded K99/R00 Pathway to Independence Award focused on a gender-affirming stigma intervention for transgender adults. She has served on editorial boards of AIDS & Behavior , The Behavior Therapist , and Journal of Contextual and Behavioral Science . Her lab, the CRAFT lab, supports collaborative research with community partners to develop evidence-based behavioral health interventions.
Matthias C. Kettemann is a full-time Professor of Innovation, Theory and Philosophy of Law at the University of Innsbruck , where he leads the Department of Legal Theory and Future of Law . He also serves as a research programme leader at the Leibniz Institute for Media Research | Hans Bredow Institute in Hamburg, research group leader at the Alexander von Humboldt Institute for Internet and Society in Berlin, and as a research group leader at the Sustainable Computing Lab in Vienna. His academic affiliations extend to associated researcher roles at institutions in Hamburg, Frankfurt am Main, and Graz. Head of Department, University of Innsbruck Research Programme Leader, Leibniz Institute for Media Research Research Group Leader, Humboldt Institute for Internet and Society Board Member, Sustainable Computing Lab Associated Researcher, Research Institute for Social Cohesion Prof. Kettemann’s research focuses on internet law , AI governance , platform regulation , digital constitutionalism , and innovation law . His publications and projects explore normative orders , multinormativity , and cybersecurity in digital spaces. His recent articles address human-in-the-loop AI systems , consumer credit algorithms , and democratic resilience against disinformation . He also investigates legal frameworks for data sovereignty and platform accountability in crisis situations . He has received prestigious scholarships, including the Fulbright and Boas Scholarships , and contributes to academic discourse as Managing Editor of the Mohr/Siebeck series 'Internet und Gesellschaft' , editorial board member of journals like jusIT and Media and Communication Studies , and scientific advisory board member of the European Yearbook on Human Rights . He is actively involved in reviewing for international publishers and academic journals. Prof. Kettemann teaches in German, English, and French, with courses in internet law , innovation law , international law , and legal philosophy since 2008. He supervises theses at bachelor, diploma, doctoral, and post-doctoral levels, emphasizing digital law and innovation frameworks . His third-party funding includes grants from the European Union , Friedrich-Ebert-Stiftung , Google , and Deutsche Telekom .
Dr. Rebecca Utz is Professor of Sociology and Criminology at the University of Utah, with adjunct appointments in Family & Consumer Studies and the College of Nursing (Gerontology). She serves as Senior Associate Dean in the College of Social and Behavioral Science and has been a faculty member since 2004. Her interdisciplinary work bridges sociology, gerontology, and health services research with practical applications for family caregivers. Dr. Utz earned her PhD in Sociology from the University of Michigan (2004) following a Master's degree in gerontology (long term care administration) from Miami University. Her academic path reflects integration of theoretical sociological perspectives with applied gerontological knowledge. Her research centers on health and aging in America, specifically examining how families manage end-of-life and chronic disease care transitions. As a lifecourse sociologist, she investigates bereavement/widowhood, family caregiving dynamics, and develops supportive interventions for caregivers, particularly in dementia care, respite services, and advance care planning. Her work consistently emphasizes community-engaged approaches that directly address caregiver needs. Dr. Utz's recent scholarship reveals an evolving trajectory toward technology-enhanced interventions for caregivers, with growing emphasis on digital inequality considerations, rural-urban disparities in caregiving resources, and innovative approaches to advance care planning for dementia patients. Her research increasingly examines how family structure influences end-of-life care experiences and outcomes. Her significant contributions have been recognized through numerous honors: Distinguished Teaching Award (2017, University of Utah) Distinguished Mentor Award (2016, University of Utah Graduate School) W. Fred Cottrell Distinguished Alumni Award (2016) Fellow, Gerontological Society of America (2012) Superior Research Award (2012) Superior Teaching Award (2010) As an educator, Dr. Utz teaches research methods, epidemiology, population studies, and families & health courses while mentoring numerous students in hands-on research experiences. Her substantial grant portfolio includes major projects like 'The Center for Dementia Respite Innovation' and 'Leading End-of-Life Dementia Care Conversations,' demonstrating sustained funding for impactful caregiver research. Dr. Utz actively contributes to research infrastructure through leadership in the Consortium for Families & Health Research and the Family Caregiving Collaborative. She serves on the Utah Special Committee of Family Caregiving and influences national policy as a delegate to the National Strategy to Support Family Caregivers, effectively bridging academic research with practical applications for family caregivers.
Marija Slavkovik is a Professor at the Department of Information Science and Media Studies, Faculty of Social Sciences, University of Bergen. She serves as Head of Department and is a leading researcher in artificial intelligence, with expertise in multi-agent systems, machine ethics, and computational social choice. Research Interests: Focuses on automating moral reasoning, ethical behavior in computational agents, and trust in algorithmic decision-making within public institutions. Grants: Leading applications for ERC Synergy Grants and managing ongoing projects like MediaFutures and Better Video Workflows via AI Techniques. Outreach: A vocal advocate for responsible AI, she participates in public debates and media discussions on AI's societal impact. Supervision: Advises doctoral students Than Htut Soe and Mina Young Pedersen, with past co-supervision of Flavio Tisi, Einar Søreide Johansen, and Hanna Kubacka. Scientific Awards: Received the Best Paper award at Norsk Informatikkonferanse 2020 for bias mitigation studies. Her work bridges logic, ethics, and AI, emphasizing societal trust, fairness, and interdisciplinary collaboration. She co-organizes Dagstuhl Seminars and serves on the editorial board of AI Magazine.
Pietro Saggese is an Assistant Professor at the IMT School for Advanced Studies Lucca, Italy, where he is affiliated with the Department of Economics and Data Science within the School of Economics, Management, and Data Science. He is also associated with the Complexity Science Hub (CSH) in Vienna, contributing to the Digital Currency Ecosystems research group. Prior to his current role, he was a postdoctoral researcher at CSH and the AIT Austrian Institute of Technology from 2021 to 2023. Bachelor’s and Master’s in Physics, University of Turin PhD in Economics and Data Science, IMT School for Advanced Studies Lucca (2021) Pietro Saggese's research centers on cryptofinance and cryptoasset analytics, with a particular focus on decentralized finance (DeFi) ecosystems. He investigates the interplay between DeFi protocols on Ethereum to assess risks and opportunities, analyzes arbitrage behavior in Bitcoin, detects financial bots on blockchains, and evaluates the governance structures of Decentralized Autonomous Organizations (DAOs). His work combines data science, complex systems theory, and economic modeling to provide empirical insights into digital currency markets. His recent publications reveal a strong trend toward understanding systemic structures in DeFi, including composability, governance centralization, and solvency risks. The works span technical blockchain analysis, economic modeling, and regulatory implications, highlighting an interdisciplinary approach to cryptoeconomic systems. Scientific Awards and Recognition: No specific awards listed in the text, though his collaborator Stefan Kitzler won a research prize for a DeFi-related paper. Pietro actively collaborates with researchers at CSH, AIT, and IMT Lucca on grants and projects related to digital currency ecosystems. His advising roles are not explicitly mentioned, but his publications suggest mentorship and collaboration with early-career researchers. He is involved in high-impact research projects on blockchain transparency, DAO governance, and financial stability in crypto markets. He is a key contributor to the Digital Currency Ecosystems research initiative at the Complexity Science Hub, where he continues to publish and present on pressing issues in decentralized finance, including power concentration in DAOs and the solvency of crypto exchanges.
Ashwin Rao is a Research Professor at the University of Southern California's Information Sciences Institute (ISI) within the Viterbi School of Engineering. With a research career spanning over two decades, his work bridges computer science, social sciences, and political science, focusing on understanding human behavior through digital footprints. His academic journey began with signal processing research in the 1990s before evolving into network protocols and mobile computing, and most recently into computational social science and AI ethics. Rao's research interests encompass Social Media Analysis, Online Political Polarization, Misinformation Detection, Network Protocols, Mobile Computing, Privacy in Mobile Applications, Natural Language Processing, and AI Ethics. His work demonstrates a consistent trajectory from technical networking research to the societal implications of technology. His most recent publications reveal a strong focus on understanding political discourse online, particularly examining polarization, emotional responses to events, and the impact of social media algorithms on information ecosystems. His interdisciplinary approach combines computational methods with social science theories to address pressing issues in digital society. Rao has published extensively across top venues including ICWSM, WWW, ACL, IEEE Transactions, and numerous conferences in networking and systems. His work often appears with Kristina Lerman, with whom he collaborates closely at USC ISI. His recent research portfolio shows a sophisticated integration of machine learning techniques with social science questions, particularly examining how language models reflect and potentially amplify societal biases. Rao has made significant contributions to understanding privacy issues in mobile applications, network protocols, and social media dynamics. His research has been influential in both technical communities studying network performance and social science communities examining online behavior. His work on BitTorrent performance, mobile privacy, and social media analysis has been widely cited across disciplines. His laboratory work appears to focus on computational social science methodologies, developing tools and frameworks for analyzing large-scale social media data while addressing ethical considerations in AI and data analysis. Recent projects suggest strong connections with public health research through social media analysis during the pandemic.
Associate Professor Yakovleva Inna Dmitrievna serves in the Department of Computer Systems and Networks at Chernivtsi National University's Faculty of Physics. With over two decades of academic experience, she has established herself as a prominent researcher in computer architecture and parallel computing. Her career progression from Assistant Professor (2003-2011) to her current Associate Professor position demonstrates her commitment to the institution and field. Her educational background includes a degree from Chernivtsi State University named after Yu. Fedkovych (Faculty of Physics, Department of Computer Science, 1993) followed by candidate studies at Lviv Polytechnic National University (2004-2007). She earned her Candidate of Technical Sciences degree in 2010 with a thesis on "Methods and tools for designing algorithmic operating devices with graphical representation of executed algorithms". Professor Yakovleva's research spans specialized computer systems, theoretical foundations of computer construction, data stream processing, algorithm development, parallelization techniques, and specialized processor design. Her work demonstrates a consistent focus on bridging theoretical computer science with practical hardware implementation, particularly through graphical representations of algorithms. She has made significant contributions to structural matrix representations of algorithm flow graphs and parallel computing architectures. Her publication record shows a strong trajectory in algorithm representation methods, evolving from foundational work on structural matrices to applications in smart home technology, voice control systems, and image processing. Recent publications indicate expanding interests in AI applications while maintaining core expertise in parallel computing and hardware design. Certificate of Appreciation from Ministry of Education (2023) 5 Years of Service Instructor Certificate (2021) Honorary Certificate from Regional Authorities (2019) Multiple EarthRover competition awards (2011-2018) Professional certifications in Linux, Cisco, and ChatGPT technologies Professor Yakovleva teaches System Software, VHDL Design Technology, Linux System Administration, and Cisco NDG Linux Essentials. Her professional development includes numerous certifications reflecting current industry trends. While the text doesn't detail specific mentoring activities, her extensive publication record with multiple co-authors suggests active collaboration with students and colleagues. Her work with research teams is evident through numerous joint publications, particularly with colleagues like Melnyk A.O. and Lisovenko I.D.
Steve Wilson is an Assistant Professor in the Department of Computer Science, Engineering, and Physics at the University of Michigan-Flint, within the College of Innovation and Technology. He holds a PhD in Computer Science & Engineering from the University of Michigan and has previously served as an Assistant Professor at Oakland University and held postdoctoral positions at the University of Edinburgh and the University of Michigan. PhD | 2019 | University of Michigan | Computer Science & Engineering M.S. | 2015 | University of Michigan | Computer Science & Engineering B.Sc. | 2013 | Taylor University | Computer Science/Systems His research focuses on understanding online communication through Natural Language Processing, with emphasis on social context, information literacy, social media narratives, and educational applications. His work bridges computer science, psychology, and social informatics to analyze human behavior in digital environments. The most recent publications highlight a strong trend in using NLP for social good, including detecting misinformation, analyzing educational discourse, improving AI ethics, and understanding social dynamics such as sarcasm, offensive language, and user profiling. His work frequently appears in top venues like ACL, EMNLP, ICWSM, and SemEval, often in collaboration with leading researchers such as Rada Mihalcea and Walid Magdy. MWIN Faculty Innovation Fellow | 2025 | UM-Flint’s Office of Economic Development and EDA University Center for Community and Economic Development UM-Flint Proposal Academy Awardee | 2025 | University of Michigan-Flint Office of Sponsored Research Projects Steve Wilson is the Principal Investigator (PI) on multiple funded research projects, including a National Science Foundation CRII grant on social media framing and an internal UM-Flint grant on AI in STEM education. He co-investigates an NSF REU site on Home Health Technology. He leads the CoCoA Lab at UM-Flint, which focuses on computational analysis of communication and context. He mentors graduate students and is actively involved in developing new courses, including a recent offering in Natural Language Processing.
David S. Ebert is a Gallogly Chair Professor of Computer Science and Electrical and Computer Engineering at the University of Oklahoma, serving as Director of the Data Institute for Societal Challenges and Associate Vice President for Research and Partnerships. He holds adjunct professorships at Purdue University and leads the Department of Homeland Security's Visual Analytics Center (VACCINE). Ebert's research focuses on visual analytics, human-AI collaboration, and trustable AI systems with applications in climate resilience, public health, and security. He earned a Ph.D., M.S., and B.S. in Computer Science from The Ohio State University. His work has led to patents in public safety systems and predictive analytics, alongside impactful tools like SMART 2.0 for social media misinformation tracking and MetricsVis for law enforcement performance evaluation. Ebert has received prestigious awards including the IEEE Visualization Technical Achievement Award and multiple Department of Homeland Security recognitions. His contributions span interdisciplinary projects addressing societal challenges such as pandemic preparedness, methane emission monitoring, and sustainable agriculture through data-driven decision systems. Key leadership roles include directing the DHS Visual Analytics Center, the Purdue Visual Analytics Center, and the Center for Education and Research in Information Assurance and Security. His research emphasizes bridging technical innovations with real-world applications in emergency response, healthcare, and environmental sustainability.
Chris Poskitt is an Associate Professor of Computer Science (Education) at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU). He also serves as Director of the BSc (IS) Smart-City Management & Technology Major and Director of Undergraduate Administration at SCIS. Dr. Poskitt is an active member of the System Analysis and Verification (SAV) research group within SCIS. Dr. Poskitt completed his PhD in 2014 at the University of York (UK) under the supervision of Detlef Plump. Prior to joining SMU, he was a postdoctoral researcher for three years at ETH Zürich, where he worked with Bertrand Meyer. His academic journey reflects a strong foundation in formal methods and software engineering principles. Dr. Poskitt's research broadly addresses the problem of engineering correct and secure software and systems. His work spans several key areas including software engineering, formal methods, cybersecurity, and computer science education. He has developed innovative techniques for testing and defending cyber-physical systems using fuzzing and machine learning, tools for analyzing execution models of concurrency APIs, and logics for reasoning about the correctness of graph-rewriting programs. His research projects include AI agent safety, autonomous vehicle testing, critical infrastructure security, defending cyber-physical systems, analyzing actor-like concurrency models, verifying graph programs, and software engineering education. Dr. Poskitt's recent publications (2024-2026) demonstrate a strong focus on safety and security of autonomous systems, particularly autonomous vehicles and LLM agents. His work combines formal methods with practical applications, addressing challenges in runtime enforcement, causality analysis, and automatic repair of system behaviors. There's a clear progression from foundational work on graph transformation and formal verification toward applied research on cyber-physical systems and AI safety, with an increasing emphasis on real-world impact. Dr. Poskitt serves as research advisor to students including Huang Shaofei, WANG Haoyu, and ZHAO Lu. His research has been supported by various grants that have enabled publications across top software engineering and security venues including ICSE, FSE, ASE, and IEEE Transactions. He has served on numerous prestigious program committees including ICSE, FSE, ASE, and ICGT, indicating recognition by his peers in the software engineering community. Dr. Poskitt is part of the System Analysis and Verification (SAV) group at SMU's School of Computing and Information Systems. This research group focuses on formal methods and verification techniques for software systems, with particular emphasis on safety and security properties. His work often involves collaboration with researchers at institutions including ETH Zürich and other international partners.
David A. Broniatowski is a faculty member in the Department of Engineering Management and Systems Engineering at the George Washington University's School of Engineering and Applied Science. His research spans systems engineering, computational social science, cognitive science, and public health, with a focus on analyzing social media to understand misinformation, decision-making, and public health communication. His research interests include systems engineering, natural language processing, fuzzy-trace theory, public health informatics, social media analytics, and misinformation detection. He investigates how people process risk and make decisions online, particularly in health-related contexts such as vaccine hesitancy and pandemic response, using computational models grounded in cognitive theory. His recent publications demonstrate a strong trend in analyzing the spread of misinformation, particularly during the COVID-19 pandemic, using NLP and machine learning. He has developed tools for measuring gist in text, detecting biases and prejudice online, and evaluating the impact of content moderation policies. His work frequently involves large-scale analysis of Twitter data and collaboration with experts in public health and computer science. Notable scientific contributions include: Developing the Twitter Social Mobility Index to measure social distancing. Creating the GisPy tool for measuring gist inference in text. Leading the creation of a large, annotated corpus of COVID-19 tweets. Applying fuzzy-trace theory to model online information spread. He has advised or collaborated with numerous researchers and students on projects related to bot detection, narrative analysis, causal reasoning in social media, and the impact of foreign influence operations. His work is supported by interdisciplinary grants focused on public health surveillance, cognitive modeling, and social computing. Dr. Broniatowski leads or is a key member of a research team that integrates systems engineering principles with data science to address complex societal challenges, particularly in the domain of public health communication and online behavior.
Darren L Linvill is a Professor at Clemson University’s College of Arts and Humanities. He serves as Co-Director of the Watt Family Innovation Center and leads the Media Forensics Hub, focusing on social media disinformation analysis and mitigation. His academic work bridges communication theory with practical digital security challenges. Research Interests : Darren’s scholarship examines social media disinformation , particularly state-sponsored influence operations and troll behavior. He analyzes how coordinated networks manipulate civil discourse, explores AI’s role in propaganda generation, and investigates the psychological impacts of inauthentic content. His interdisciplinary approach combines political communication, cybersecurity, and media studies. Academic Background : Ph.D., Clemson University (2008) M.A., Wake Forest University (2002) B.A., Wake Forest University (1999) Recent Work Trends : His publications reveal a focus on AI-enhanced disinformation strategies, cross-border troll activities, and digital influence in geopolitical conflicts. Key themes include troll identity manipulation, algorithmic propaganda amplification, and the intersection of technology with political discourse. Public Engagement : Beyond academia, Darren contributes to mainstream media outlets like The Washington Post , Foreign Affairs , and Lawfare , translating technical findings into accessible policy discussions.
Javier Pastor Galindo is a researcher at the University of Murcia's Department of Information and Communications Engineering, affiliated with the Faculty of Informatics. He holds B.Sc., M.Sc., and Ph.D. degrees in Computer Science from the same institution. His roles include FPU-MECD Predoctoral Researcher (2019–present) and later postdoctoral researcher, specializing in cybersecurity, cyberintelligence, and disinformation analysis. He leads projects like DEFENDER (cybersecurity in IoT/5G labs), CDL-TALENTUM (cybersecurity talent development), and EUCINF (EU cyber warfare tools). Education: PhD in Computer Science (in progress), University of Murcia MSc in New Technologies on Computer Science (2019), specialization in Networks and Telematics BSc in Computer Science Engineering (2018), specialization in Information Technologies Research Interests: Focus on OSINT, cyber defence, disinformation detection, and social media analysis. His work spans frameworks for bot detection (e.g., BOTTER), Tor network studies, and NLP-based threat analysis. He emphasizes practical applications, such as the INDRA Cyber Range training platform. Awards: Recipient of the prestigious FPU Predoctoral Grant (2019), Research Initiation Grant (2018), and academic distinctions for his thesis work on SDN and TLS security. His research aligns with EU and national defense initiatives, addressing critical cybersecurity challenges. Grants & Projects: Involved in high-budget projects (e.g., EUCINF: €41M, EU-GUARDIAN: €13.5M), focusing on AI-driven cyber defence automation and European cyber resilience. Collaborates with entities like INCIBE and the European Defence Fund. Labs & Teams: Part of the CyberDataLab UMU, a hub for cybersecurity and data science R&D. Engages in interdisciplinary efforts, such as the COnVIDa pandemic data dashboard.
