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Siwei LyuView profile

Professor

• Digital Media Forensics
• Computer Vision
• Machine Learning
• +4 more

Dr. Siwei Lyu is a SUNY Distinguished Professor and SUNY Empire Innovation Professor in the Department of Computer Science and Engineering at the University at Buffalo. He serves as Co-Director of the Center for Information Integrity (CII) and Director of the UB Media Forensic Lab (UB MDFL). His research focuses on digital media forensics, computer vision, and machine learning, with significant contributions to counter-deepfake technologies. Education includes a PhD in Computer Science from Dartmouth College (2005), MS from Peking University (2000), and BS in Information Science from Peking University (1997). He has held academic positions at the University at Albany and New York University. His work spans media forensics, adversarial machine learning, and AI security. Notable achievements include developing the Celeb-DF dataset, leading NSF-funded projects, and testifying before U.S. and NYS legislative bodies on disinformation threats. Over $11.3M in grants have supported his research on AI-generated media detection, including a $5M NSF Convergence Accelerator grant. Key awards include IEEE and IAPR Fellowships, Google Faculty Award, and SUNY Chancellor's Research Award. He has authored 230+ papers, 4 patents, and serves on editorial boards of top journals and conferences (e.g., CVPR, ICCV).

Lynn WuView profile

Associate Professor

• Artificial Intelligence
• Enterprise Social Media
• Innovation
• +6 more

Lynn Wu is an Associate Professor at the Wharton School of the University of Pennsylvania, focusing on the intersection of artificial intelligence, analytics, and innovation. She teaches MBA, undergraduate, and doctoral courses on emerging technologies' transformative impact on business and society. Education: B.S. in Finance and Computer Science, MIT M.S. in Computer Science, MIT Ph.D. in Management Science, MIT Sloan Her research explores how AI and digital platforms reshape productivity, workforce dynamics, and innovation strategies, with applications in antitrust policy and startup ecosystems. Key trends in her publications include AI's role in post-IPO innovation, robotics' impact on managerial roles, and social media's ability to mitigate funding disparities. Scientific Awards: Kauffman Best Paper Award (2019) Sandy Slaughter Early Career Award (2019) AIS Early Career Award (2018) ISR Best Published Paper (2014) Best Paper Awards at ICIS (2009), HICSS (2013), etc. She has collaborated with IBM, Google, Meta, and advised the U.S. Department of Justice and World Bank, with her work cited by The New York Times , The Economist , and Harvard Business Review .

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +7 more

Barbara Plank is a full professor and chair for AI and Computational Linguistics at Ludwig Maximilian University of Munich (LMU), where she heads the Munich AI and NLP (MaiNLP) lab and co-directs the Center for Information and Language Processing (CIS). She additionally serves as a visiting full professor at the IT University of Copenhagen, maintaining active dual institutional affiliations in computational linguistics and NLP research. Her research focuses on human-centric natural language processing challenges, particularly learning under sample selection bias (domain adaptation, transfer learning) and annotation bias, learning with limited data through continual/semi-supervised/weakly-supervised methods, multimodal learning at language-vision-speech interfaces, and fortuitous supervision for variety-space aware language understanding. She pioneers methodologies addressing human label variation as a critical factor in model robustness rather than mere noise. Recent publications (2024-2025) reveal dominant trends in modeling human label variation across NLP tasks, especially natural language inference and entity recognition, alongside dialectal language processing and LLM evaluation frameworks. Her work systematically investigates how human disagreement in annotations can be leveraged to build more robust, adaptable systems rather than treated as errors. Scientific recognition includes: ERC Consolidator Grant for the DIALECT project advancing natural language understanding for non-standard languages and dialects ACL 2024 Area Chair Award for the paper 'VariErr NLI: Separating Annotation Error from Human Label Variation' Leading the MaiNLP lab at CIS (LMU), she directs research integrated with MCML (Munich Center for Machine Learning), Munich Intelligent Robotics, ELLIS Unit Munich, UniDive, and COST action. Current projects include ERC-funded DIALECT and KLIMA-MEMES, focusing on human-facing NLP solutions for real-world language diversity challenges. She actively shapes the field through ACL leadership as VP-Elect and numerous keynotes emphasizing human-centric approaches. The MaiNLP lab at Akademiestr. 7, 80799 Munich, drives innovation in computational linguistics through interdisciplinary collaboration, maintaining strong ties with European research networks while developing practical applications for language variation and robust NLP systems. The lab's work directly informs her teaching in LMU's Computational Linguistics programs, bridging research and education in cutting-edge NLP methodologies.

Barbara J. GroszView profile

Research Professor

• Artificial Intelligence
• Natural Language Processing
• Multi-agent Systems
• +4 more

Barbara J. Grosz serves as Higgins Research Professor of Natural Sciences in Harvard University's School of Engineering and Applied Sciences, renowned for foundational contributions to Artificial Intelligence through pioneering work in dialogue processing and multi-agent collaboration theories applied to human-computer interaction, healthcare coordination, and science education. Her research spans Artificial Intelligence, Natural Language Processing, Multi-agent Systems, and Computational Ethics, with recent focus on improving computer system design for healthcare and education. She co-founded Harvard's Embedded Ethics program, which integrates ethical reasoning into core computer science curricula, reflecting her commitment to responsible AI development. Professor Grosz has earned exceptional recognition including: ACM/AAAI Allen Newell Award (2009) IJCAI Award for Research Excellence (2015) ACL Lifetime Achievement Award (2017) Election to the National Academy of Engineering Membership in the American Philosophical Society Her leadership extends to establishing interdisciplinary research institutions and advancing women in science, demonstrating sustained impact across academia and societal applications of AI.

Steff LewisView profile

Professor

• Medical Statistics
• Clinical Trials
• Epidemiology
• +3 more

Steff Lewis is a Professor of Medical Statistics at the University of Edinburgh , affiliated with the Usher Institute within the College of Medicine and Veterinary Medicine . She leads the statistics group at the Edinburgh Clinical Trials Unit and holds roles in the Deanery of Molecular, Genetic and Population Health Sciences . Her expertise spans meta-analysis, randomized trial design, and clinical trial governance, with involvement in Cochrane Collaboration and UK Clinical Research Collaboration initiatives. Education: MSc and PhD in Medical Statistics. Research Interests: Focuses on methodological advancements in clinical trial reporting (e.g., CONSORT and SPIRIT guidelines), cardiovascular outcomes (e.g., SCOT-HEART trial), stroke prevention (ASPIRING trial), and ethical data management. She actively contributes to international standards for trial protocols, anonymization practices, and statistical validation. Recent Contributions: Over 200 peer-reviewed articles and 37 ongoing projects, including leadership in trials assessing antiplatelet therapies, Paget’s disease interventions, and pediatric asthma treatments. Collaborates globally on guidelines for randomized trials and data-sharing protocols. Grants & Teams: Principal or co-investigator on projects funded by NIHR, BHF, and ESRC, including trials on iron therapy in critical care (INTACT-2) and cannabinoid treatments for endometriosis pain (ENDO-CAN). Leads multidisciplinary teams integrating statistical rigor with clinical innovation. Labs/Teams: Embedded within the Edinburgh Clinical Trials Unit and the Centre for Population Health Sciences , fostering collaborative research across molecular, genetic, and public health domains.

• Statistical Network Analysis
• Machine Learning
• Data Privacy
• +7 more

Tianxi Li is an Assistant Professor in the Department of Statistics at the University of Minnesota, Twin Cities, within the College of Science and Engineering. Their research integrates statistical methodology with applications in network science, data privacy, and biomedical data analysis. Their research interests lie at the intersection of statistics and network science, focusing on statistical modeling of complex networks , data privacy , network security , and biomedical applications such as neuroimaging and genomics. They develop adaptive and scalable methods for network estimation, community detection, and differential correlation analysis. The recent publications demonstrate a consistent focus on advancing statistical tools for network-structured data, with increasing applications in neuroscience and cancer genomics. The work spans theoretical development (e.g., network growth models) and practical applications (e.g., glioblastoma gene modules), reflecting a balance between methodology and real-world impact. Tianxi Li leads an active research program funded by the National Science Foundation, indicating recognition and support for their innovative work. Principal Investigator, Statistical tools for network security protection: from data privacy to threat detection , NSF (2024–2025) They advise graduate students in statistics and data science, though specific advisees are not listed. Their collaborative network includes researchers in biostatistics, computer science, and machine learning, as evidenced by co-authorships and interdisciplinary projects. Li's work contributes to the UN Sustainable Development Goals, particularly through advancements in data-driven solutions for secure and ethical data analysis.

Jonathan CookView profile

Research Fellow

• Malaria Eradication
• Emerging Infectious Diseases
• Structure-Based Vaccine Design
• +3 more

Dr Jonathan Cook is a Research Fellow at Jesus College, University of Oxford, affiliated with the Medical Sciences division. He holds a primary medical qualification from Queen’s University (Canada, 2021) and a PhD investigating viral immune evasion mechanisms under Prof Jeffrey Lee. His work was supported by the Vanier Canada Graduate Scholarship and recognized with the Stuart Alan Hoffman Memorial Prize. As an incoming Banting Fellow at the Jenner Institute, he focuses on vaccine design for infectious diseases. His research interests include malaria eradication, emerging pathogens, and structure-based vaccine strategies. **Education**: - PhD (Investigation of viral entry glycoproteins), University of Toronto, supervised by Prof Jeffrey Lee - Primary Medical Qualification, Queen’s University, Canada **Research Interests**: - Malaria Eradication : Developing vaccines targeting Plasmodium species. - Emerging Infectious Diseases : Designing rapid-response strategies for pathogens like SARS-CoV-2. - Structure-Based Vaccine Design : Leveraging protein structural data to enhance immunogenicity. **Awards**: - Vanier Canada Graduate Scholarships Programme (2017–2020) - Stuart Alan Hoffman Memorial Prize (2021) - Banting Fellowship (incoming) **Grants/Advising**: Works on Jenner Institute-funded projects. No listed advisees yet. **Labs/Teams**: Collaborates with Prof Lee's lab at the Jenner Institute and the University of Toronto's Medical Microbiology program.

Maya BalakrishnanView profile

Assistant Professor

• Operations Management
• Artificial Intelligence
• Supply Chain Management
• +3 more

Maya Balakrishnan is an Assistant Professor of Operations Management at the Jindal School of Management (JSOM), University of Texas at Dallas. She holds a PhD in Business Administration from Harvard Business School (2024) and a BS in Computer Science from Stanford University (2016). Her primary research focuses on Human-AI collaboration, Corporate Social Responsibility, and Behavioral Operations Management. She teaches courses such as AI in Supply Chain Management (OPRE 4393) and Advanced AI in Supply Chain Management (OPRE 6383). Her research explores how humans interact with algorithms in operational contexts and the ethical implications of workforce diversity disclosures on consumer behavior. Recent work emphasizes trust-building through operational design and mitigating risks in human-AI systems. Her awards include multiple first-place recognitions in behavioral operations competitions and a best presentation award at the Advances in Decision Analysis Conference. Awards: 2024 Production and Operations Management Junior Scholar Paper Competition (1st Place) 2023 INFORMS Behavioral Operations Working Paper Competition (2nd Place) 2022 Best PhD Blitz Presentation (Advances in Decision Analysis) Dr. Balakrishnan is actively involved in professional organizations such as INFORMS and the Manufacturing and Service Operations Management Society (MSOM). Her work bridges behavioral insights with operational systems, addressing real-world challenges in AI ethics and supply chain innovation.

• Web Security
• Software Security
• Secure Programming
• +3 more

Prof. Dr. Martin Johns serves as Chair of Application Security at the Institute for Application Security within the Carl Friedrich Gauss Faculty at Technical University Braunschweig. He joined TU Braunschweig after working as Research Expert at SAP Security Research, where he shaped security strategy and led software security teams. Prior to SAP, he worked as software engineer in Germany at companies like TC Trustcenter and Infoseek Germany. Academic qualifications include a PhD in Computer Science (University of Passau, 2009) and a Diploma in Computer Science (University of Hamburg, 2003). His research focuses on web security and software security , particularly secure programming , vulnerability detection , and attack mitigation strategies. Recent publications cover topics like GDPR compliance frameworks , WebAssembly security , federated learning privacy , and server-side request forgery (SSRF) defenses. His work appears in top conferences including IEEE S&P, CCS, WWW, and ACM CODASPY.

Ian RuthvenView profile

Professor

• Information Seeking Theory
• Human-Computer Interaction
• User Studies
• +7 more

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 VarolView profile

Assistant Professor

• Computational Social Science
• Network Science
• Machine Learning
• +4 more

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.

• Artificial Intelligence
• Data Science
• Machine Learning
• +5 more

Lizi Liao is an Assistant Professor at the School of Computing and Information Systems , Singapore Management University (SMU) , specializing in Artificial Intelligence and Conversational AI . Her research bridges Machine Learning , Natural Language Processing , and Multimodal Systems , focusing on proactive dialogue systems, multimodal conversational search, and task-oriented interactions. Education : PhD in Computer Science (2019) from the National University of Singapore (NUS) , advised by Professor Tat-Seng Chua . Research Interests center on principles of human conversational understanding and machine implementation, particularly in proactive conversational agents , multimodal dialogue systems , and target-driven conversation planning . Key applications include emotional support systems , intelligent shopping assistants , and learning companions . Recent Publications (2024-2025) highlight her work on LLM-based proactive dialogue , multimodal emotion recognition , and dynamic graph modeling , often integrating NLP , Multimedia , and Knowledge Graphs . Collaborative projects with her CoAgent Lab team emphasize human-AI interaction and ethical response generation . Scientific Awards : Google South Asia & Southeast Asia Research Award 2023 Lee Kong Chian Fellow Teaching includes Visual Analytics for Business Intelligence (undergraduate) and Text Analytics and Application (graduate). She also serves as Associate Editor for TOIS and TOMM , and organizes tutorials at ACL , SIGIR , and WSDM .

George BuchananView profile

Professor

• Human-Computer Interaction
• Digital Libraries
• Information Retrieval
• +5 more

Professor George Buchanan is a leading researcher in human-computer interaction and digital libraries at RMIT University . His work bridges information science, digital humanities, and health informatics, focusing on usability in sensitive contexts like healthcare and misinformation. Deputy Dean, Research at RMIT University Former Director, University of Melbourne iSchool Research Interests: Digital information interaction Health and aging informatics Disinformation analysis Mobile interface design Digital library systems Key Contributions: Developed mobile web usability benchmarks, spatial hypertext tools, and thermal feedback interfaces. Currently seeking PhD students for 2025 projects on digital browsing and view change dynamics. Awards: Over twenty best paper awards and Honorary Life Fellow of the Royal Society of Arts. Advising: Accepting Masters/PhD supervision in information interaction and digital health domains.

• platform governance
• digital policy
• artificial intelligence
• +6 more

Professor Terry Flew (BEc (Hons), MEc (Sydney), MBA (QUT), PhD (Griffith)) is a leading academic at the University of Sydney , holding the Professor of Digital Communication & Culture position within the Faculty of Arts and Social Sciences . As an Australian Research Council Laureate Fellow (2024-2029), he leads the Centre for AI, Trust & Governance , a flagship initiative involving multiple faculties. His international appointments include Research Fellow at the UK Creative Industries Policy & Evidence Centre and Honorary Professor at the University of Nottingham Ningbo China. Co-Director, Centre for AI Trust and Governance Member, SSSHARC research center International collaborations with Carleton University (Canada), Communications University of China, University of Glasgow (UK) Research Focus : Specializing in platform governance , digital policy , and mediated trust , Professor Flew bridges media economics , AI ethics , and creative industries . His work examines digital platform regulation , news media sustainability , and global internet governance , with recent projects analyzing trust mechanisms in AI systems and digital content regulation . The 2024-2028 Laureate Fellowship on "Mediated Trust" integrates these themes. Publications & Grants : With 16 authored/edited books and 129 journal articles , he has secured $11 million in research funding (including $9.9 million from ARC). Key grants include ARC Discovery projects on digital platform governance and Linkage projects on citizen journalism. Professional Leadership : Served as ICA President (2019-2020), ANZCA President (2009-10), and Lead Commissioner for the Australian Law Reform Commission. Currently sits on editorial boards of Journal of Communication , Global Media and Communication , and Media International Australia .

Shintaro OkazakiView profile

Professor

• Marketing Communications
• Digital Marketing (AI, Mobile, Social Media)
• Social Issues in Marketing (Diversity, Sustainability)
• +2 more

Shintaro Okazaki is a Professor of Marketing at King’s Business School, King’s College London. He holds a PhD from the Autonomous University of Madrid and has over 20 years of industry experience, including roles at a multinational corporation in Tokyo. His research focuses on marketing communications, digital marketing, social issues in marketing, international marketing strategies, and tourism marketing. He has authored over 100 articles and chapters, with a strong emphasis on advertising, AI ethics, sustainability, and consumer behavior. Research Interests: Marketing Communications: Advertising, Branded Entertainment, Cross-Cultural Advertising, Emotions in Advertising Digital Marketing: AI, Mobile Marketing, Social Media Marketing, Digital CSR Social Issues: Diversity, LGBTQ+ Inclusion, Disaster Resilience, Media Addiction, Sustainability International Marketing: Deglobalisation, Global Brand Positioning, Marketing Standardisation Travel & Tourism: Sustainable Tourism, Greenhushing, Peer-to-Peer Accommodation Awards & Roles: Former Editor-in-Chief of Journal of Advertising (2014–2019) Past-President of the European Advertising Academy Editorial Board Member for Journal of Public Policy & Marketing , International Marketing Review , and others Recipient of multiple awards, including the 2010 Journal of Advertising Best Article Award Grants & Conferences: Grant panelist for over 20 international organizations Organized/chaired 30+ academic conferences globally Labs & Teams: Research Lead of the Department of Marketing at King’s Business School, leading interdisciplinary projects on AI ethics, crisis communication, and sustainable marketing strategies.