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Martin Muderspach ThellefsenView profile

Associate Professor

• Epistemology of information
• Knowledge and classification
• Knowledge organization theory and systems
• +6 more

Martin Muderspach Thellefsen is an Associate Professor at the Department of Communication within the Faculty of Humanities at the University of Copenhagen. His research critically examines the philosophical foundations of knowledge organization systems through the integration of pragmatic semiotics (Peircean tradition) and domain-analytic frameworks. Thellefsen investigates how assumptions about reality shape information systems, advocating for epistemologically sound and ethically responsible design principles. Education: 2010: PhD, Royal School of Library and Information Science, Aalborg 1998: Master of Library and Information Science (MLISc) 1994: Supplementary Education in Rhetoric, Communication and Mediation 1990: Graduated Librarian Research Focus: Thellefsen's work centers on the tension between technological classification approaches and socially constructed knowledge. Core areas include epistemology of information, knowledge organization systems, pragmatic semiotics, sociotechnical systems, and critical analysis of information technologies. His research emphasizes context-aware frameworks that accommodate the dynamic nature of human meaning-making. Publications: Thellefsen's recent articles demonstrate a consistent focus on semiotic analyses of information concepts, knowledge representation, and interdisciplinary boundaries in information science. His works frequently revisit foundational theories (e.g., Belkin's information concept) through pragmatic semeiotic lenses, exploring ontological commitments and epistemological implications across evolving knowledge organization paradigms.

Jens-Erik MaiView profile

Professor

• Philosophy of Information
• Information Ethics
• Privacy Studies
• +7 more

Jens-Erik Mai is Professor of Information at the Department of Communication, University of Copenhagen. He has previously served as Head of Department for both the Department of Communication (2019-2025) and the Department of Information Studies (2017-2019) at the University of Copenhagen. Prior to his current position, he was Associate Professor at the Faculty of Information, University of Toronto (2006-2012), where he also served as Vice Dean (2006-2009) and Acting Dean (Fall 2008). Earlier in his career, he was Assistant Professor at the Information School of the University of Washington (2000-2006), where he co-directed the Center for Human-Information Interaction (2003-2006). He earned his Ph.D. in Information Science from the School of Information at the University of Texas at Austin in 2000 as a Fulbright Scholar, with additional degrees from the Royal School of Library and Information Science in Denmark. Mai's research addresses fundamental questions about data and information in the digital society, exploring philosophical, ethical, cultural, and contextual dimensions of information systems, digital media, and cultural institutions. His work has significantly impacted philosophy of information, information ethics and privacy, and knowledge organization/classification. He has made notable contributions to understanding information quality from a Gricean perspective and analyzing the concept of personal information in the context of datafication. His recent publications (2020-2025) demonstrate a strong focus on privacy, identity, and ethics in digital society, with recurring themes examining how digital technologies reshape human identity, privacy concepts, and social structures. His work bridges information science, philosophy, ethics, and social theory, creating an interdisciplinary approach to contemporary information challenges. Philosophical highlights in 2021 Mai actively participates in the international information science community as conference chair, workshop organizer, reviewer, editor, speaker, and editorial board member for the Journal of Documentation, Aslib Journal of Information Management, and Journal of Education for Library and Information Science. As Principal Investigator for the interdisciplinary research project 'Don't Take it Personal' – Privacy and information in an algorithmic age, supported by Independent Research Fund Denmark, he has supervised numerous students and research collaborators. His work has been referenced in policy sources and has gained attention across academic platforms. He maintains an active public presence through media interviews and contributions to public discourse on information science topics, demonstrating his commitment to knowledge dissemination beyond academic circles.

Laura SkouvigView profile

Associate Professor

• Information History
• History of Knowledge
• Surveillance History
• +4 more

Laura Skouvig is an Associate Professor in the Department of Communication at the Faculty of Humanities, University of Copenhagen, with 59 research outputs and 55 professional activities spanning information history, surveillance studies, and knowledge history. Her research examines how information is understood, used, and organized across historical periods, focusing on the evolution of information concepts through book history, library history, and media history. She investigates power dynamics in information systems and the commercialization of knowledge, bridging cultural and social historical perspectives. Recent publications (2020-2026) reveal consistent exploration of information historiography, surveillance across eras from antiquity to digital contexts, and the commodification of information. Her work demonstrates methodological innovation through rhetorical genre theory and interdisciplinary approaches to knowledge production. Skouvig supervises student research on information history and surveillance topics. As Principal Investigator of the DFF-funded "Objects of Knowledge" network (2025-2027), she leads collaborative research advancing historical epistemology. She organizes major conferences including "The Eyes and Ears of Power" on surveillance history. She directs the "Objects of Knowledge" research network, fostering international collaboration to develop theoretical frameworks for studying knowledge formation across cultures and historical periods.

Yunseon ChoiView profile

Associate Professor

• Knowledge Organization
• Metadata
• Ontologies
• +6 more

Dr. Yunseon Choi serves as Associate Professor at Valdosta State University, specializing in Library and Information Science with research focusing on knowledge organization systems. Her academic work centers on metadata, ontologies, and linked data applications in social media and children's literature contexts. Her educational background includes: Ph.D. in Library and Information Science, University of Illinois at Urbana-Champaign (2011) M.A. in Library and Information Science, Yonsei University (1999) Bachelor of Library Science, Chung-Ang University (1995) Dr. Choi's research program investigates how knowledge organization principles apply to contemporary digital environments, particularly examining reader-generated content in social media and online book reviews. She develops methods to extract meaningful metadata from unstructured discussions about children's multicultural literature, creating bridges between computational analysis and traditional cataloging practices. Her work aims to improve book recommendation systems through sentiment analysis and feature clustering techniques. No scientific awards were mentioned in the available documentation. Dr. Choi actively contributes to the academic community through committee service in professional organizations including ALISE, ASIS&T, and the iConference. While specific grant information isn't provided, her consistent publication record in top-tier journals and conferences demonstrates active research productivity. She teaches foundational courses in information organization, classification, and metadata systems. Based in the Odum Library at Valdosta State University, Dr. Choi collaborates with professional organizations rather than maintaining a formal research laboratory. Her work connects theoretical knowledge organization frameworks with practical applications in digital library environments, particularly focusing on children's literature discovery systems.

Joanna P. KimbellView profile

Assistant Clinical Professor

• Business Law
• Fraud Examination
• Internal Controls
• +3 more

Joanna P. Kimbell serves as Clinical Assistant Professor of Business Law and Management at West Texas A&M University's Paul and Virginia Engler College of Business, holding the Patterson Professorship of Business Law since 2025. She teaches Business Law, Law & Economics, Conflict Resolution & Negotiation, and Strategic Management across 2-3 course sections per semester, with Spring 2026 schedules including three Business Law sections. Her academic foundation includes: J.D. and M.B.A. in Business Law and Management from Baylor University (2008) B.S. in Economics from Butler University (2000), where she earned Outstanding Economics Senior honors Dr. Kimbell's research centers on fraud examination, internal controls, and business strategy, examining legal-business intersections through real-world case studies. Her publications analyze cybersecurity provider policies (Cloudflare/Kiwi Farms), employment law challenges (background checks, pay equity), and anti-corruption frameworks (FCPA/COSO). She bridges theoretical legal principles with corporate practice through her dual attorney and auditor certifications. Her recent scholarly output reveals evolving focus areas: early work concentrated on SEC rulemaking and legal pedagogy (2016-2017), expanding to technology-law intersections (employee tracking, Section 230) by 2020, and currently addressing contemporary issues like online content moderation and hiring equity. This progression demonstrates consistent engagement with emerging legal-business dilemmas while maintaining core expertise in fraud and controls. Dr. Kimbell actively mentors undergraduate students, advising 20-30 per term since 2016 with documented capstone projects like Pedro Lameiras Dos Santos' ethical leadership study. She serves on multiple university committees including Faculty Development (2024-2027) and Strategic Planning (2017-2027), while contributing professional service through journal reviewing and Texas Library Coalition representation. Though not leading a formal research laboratory, she integrates students into scholarly work through co-authored publications and case competition mentorship. Her creative practice as fiction author Maryanne M. Wells (including the 'Undead Bar Association' series) complements academic work by exploring legal-historical narratives through mythological lenses.

• Machine Learning
• Statistics
• Artificial Intelligence
• +6 more

Michael Irwin Jordan is a Professor at the University of California, Berkeley, ranked #1 worldwide in Machine Learning and Distributed Computing, #36 in Computer Science, and #9 in Statistics according to Academic Influence rankings. His interdisciplinary research bridges theoretical foundations with practical applications across machine learning, statistics, and artificial intelligence. His educational background includes a PhD in Computer Science from the University of California, San Diego, a Master's in Mathematics from Arizona State University, and a Bachelor's in Psychology from Louisiana State University. This diverse foundation has shaped his approach to integrating perspectives from computer science, statistics, neuroscience, and psychology. Professor Jordan's research spans several decades, beginning with foundational work in neural networks and connectionist models. He made seminal contributions to probabilistic graphical models, variational inference, and Bayesian nonparametrics. His 2001 paper 'Latent Dirichlet Allocation' has received over 34,000 citations, becoming one of the most influential papers in machine learning. More recently, his work has focused on applications to biological data analysis, particularly single-cell transcriptomics, where he has developed probabilistic models and software tools like scvi-tools. Member of the National Academy of Engineering (2010) Ranked #1 worldwide in Machine Learning Ranked #1 worldwide in Distributed Computing Ranked #36 worldwide in Computer Science Ranked #9 worldwide in Statistics As an advisor, Professor Jordan has mentored numerous PhD students who have become leaders in academia and industry. His recent work through 2022 shows continued innovation across multiple domains, including uncertainty quantification, theoretical analysis of transfer learning, and scalable frameworks for reinforcement learning. He also contributes significantly to data science education, having helped develop Berkeley's undergraduate data science curriculum.

Brice ChardinView profile

Associate Professor

• Data Engineering
• Clustering Algorithms
• Query Relaxation
• +5 more

Brice Chardin is an Associate Professor in Data Engineering at ISAE-ENSMA since 2013, affiliated with the LIAS (Laboratoire d'Ingénierie des Applications de la Connaissance et des Systèmes) Data and Model Engineering team. His work bridges academic research and industrial applications, focusing on data management solutions for critical systems. His research spans clustering algorithms under dissimilarity constraints , RDF query relaxation for explaining empty/overabundant results, pattern mining through the RQL language, and energy data management . Key projects include Chronos (a NoSQL system for industrial sensor data) and collaborations with energy companies SRD and Nexeya for predictive consumption analysis. Recent publications (2021-2024) emphasize constrained clustering techniques and cooperative query processing for RDF knowledge bases, revealing a strong trend toward practical solutions for industrial data challenges. His work integrates machine learning with database theory to address real-world data imperfections. PhD in Computer Science from INSA Lyon (2011) Postdoctoral position at LIRIS (2012-2013) on ANR DAG project Specialized in industrial data management since 2011 EDF collaboration Chardin actively supervises academic projects including drone simulation with Ardupilot and Smart Data mining initiatives. His industrial partnerships focus on energy sector applications, particularly predictive analysis for electricity distribution and storage systems. Current work involves developing clustering algorithms with error bounds and query relaxation frameworks for semantic web technologies.

Jie LiuView profile

Professor

• Big Data Intelligent Analysis
• Machine Learning Systems
• Intelligent Software Engineering
• +3 more

Jie Liu is a Researcher at the Institute of Software, Chinese Academy of Sciences and a Professor and Doctoral Supervisor at University of Chinese Academy of Sciences. He is also a Member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences and an Executive Committee Member of the System Software Committee of the CCF Computer Society. His research is conducted within the Software Engineering Technology R&D Center. Dr. Liu received his Ph.D. from the University of Science and Technology of China in 2011 and his B.A. from the same institution in 2004. He has progressed through the ranks at the Institute of Software, CAS, starting as an Assistant Research Fellow (2011-2014), then Associate Research Fellow (2014-2024), and currently as a Researcher (since 2024). His research spans Big Data Intelligent Analysis Models and Systems at the intersection of AI, Software Engineering, and System Software. Specifically, his work covers three main areas: Big Data and Machine Learning Systems (statistics and AI algorithm model libraries, data quantitative analysis tools, LLM reasoning optimization, Earth Big Data); Intelligent Software Engineering (code model constraint decoding, data science agents, system log analysis agents); and Knowledge-Enhanced Intelligent Model Construction (knowledge extraction, knowledge graphs, domain AI model design). His research has resulted in innovative approaches to handling complex data analysis challenges across multiple domains. Dr. Liu's research has produced significant outcomes including EarthDataMiner, which supports SDG indicator calculations and won the 2024 Beijing Municipal Science and Technology Progress First Prize. His work on RISC-V software migration technology has been integrated into the Ruiqian tool (https://rvpt.top/), demonstrating practical applications of his research in emerging computing architectures. Beijing Science and Technology Progress Award, First Prize, 2024 2023 Surveying and Mapping Science and Technology Award, Special Prize, 2023 DASFAA Best Paper Runner-up, Second Prize, 2013 Dr. Liu has successfully guided numerous graduate students who have secured positions at major technology companies including Alibaba, ByteDance, Southern Power Grid, and Agricultural Bank of China. He has secured funding through multiple National Natural Science Foundation projects, National Key R&D Program projects, and over ten other research initiatives. His research collaborations span industry leaders like Huawei, JD.com, and TravelSky, as well as academic institutions within the Chinese Academy of Sciences. He teaches graduate courses such as 'Machine Learning Systems' and 'Cloud Computing and Big Data Technology' at University of Chinese Academy of Sciences, and has established a research group focused on developing innovative solutions at the intersection of AI and software engineering with real-world applications in earth sciences, healthcare, and intelligent systems.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Associate Professor Tham Piumsomboon is a prominent researcher at the University of Canterbury's School of Product Design within the Faculty of Engineering. With a PhD in Computer Science from the same institution, their work bridges gaming, human-computer interaction, and immersive VR/MR/AR technologies to enhance user experiences and redefine lifestyle interactions. As founder of the QUADRIC Research Group, they lead initiatives addressing Aotearoa's agricultural, mental health, and sustainability challenges through intuitive intelligent user interfaces. Research focuses on the intersection of human qualia and technological design, emphasizing experiential learning, cognitive modeling, and ethical AI alignment. Key research thrusts include 'Agents' (AI autonomy levels), 'Humans' (IUIs for XR collaboration), 'Augment' (enhancing human perception), and 'Aotearoa' (local solution development). Their publications reveal strong trends in spatial interaction techniques, remote collaboration frameworks, and mental health applications of XR technologies. ACM CHI 2018 Best Paper Award for 'Pinpointing' research New and Emerging Researcher Award 2022 Extensive editorial service for IEEE TVCG, ACM SIGGRAPH, and UIST conferences As principal investigator for three major grants including 'Tōku Hoa: A Personalized Agent for Mental Health' (MBIE, 2022-2025) and 'Navigating Well-being' (Child Well-being Research Institute, 2024), they direct significant research funding toward mental health and agricultural technology. They supervise over 15 graduate students across diverse XR projects from locomotion techniques to therapeutic applications. The QUADRIC Research Group serves as their primary laboratory environment, fostering interdisciplinary collaboration between computer science, design, and clinical domains.

• Software Evolution
• Empirical Software Engineering
• Domain-Specific Languages
• +2 more

Thomas Degueule is a researcher at CNRS (Centre National de la Recherche Scientifique) in France, actively contributing to software engineering research since 2015. He serves on program committees for major conferences including ASE, ICSE, and SLE, with primary research interests in Software Evolution, Empirical Software Engineering, and Domain-Specific Languages. His work focuses on breaking change analysis in APIs and libraries, client-library compatibility testing, and dependency management. He develops practical tools like Roseau for source-based breaking change detection and investigates semantic versioning impacts in ecosystems like Maven Central. His empirical approach leverages large-scale repository analysis to address real-world software maintenance challenges, particularly in Java ecosystems. Recent publications (2023-2025) show consistent contributions to breaking change analysis and compatibility testing, appearing in top venues like ASE, ICSE, and ISSTA. His research bridges theoretical insights with practical tooling for software evolution challenges, demonstrating strong empirical methodology and tool-oriented contributions. No scientific awards are documented in the available information. Degueule has advised no publicly listed students and holds no mentioned research grants. His organizational roles include Program Co-Chair for SLE 2023 and committee positions across multiple conferences, reflecting significant service to the software engineering community.

• Protein engineering
• Chemical biology
• Peptide/protein chemistry
• +7 more

Julio A. Camarero is a Professor in the Department of Pharmacology and Pharmaceutical Sciences at the University of Southern California's Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences. He holds the John A. Biles Professorship in Pharmaceutical Sciences and leads a research program focused on protein engineering, chemical biology, and peptide therapeutics. Dr. Camarero obtained his PhD from the University of Barcelona and completed postdoctoral training at The Rockefeller University as a Burroughs Wellcome Fellow. He served as a Distinguished Lawrence Fellow at Lawrence Livermore National Laboratory before joining USC in 2008 as an Associate Professor. His research focuses on developing chemical biology approaches using protein splicing and synthetic protein chemistry to study cancer and bacterial pathogenicity. His lab is renowned for pioneering work with cyclotides - small, disulfide-rich cyclic peptides with remarkable stability. Dr. Camarero's research has advanced cyclotide synthesis, engineering for drug design, and understanding of their folding and stability. His work explores applications as antimicrobial agents against multidrug-resistant pathogens, anticancer therapeutics targeting CXCR4, p53, and RAS/RAF pathways, and CNS drug delivery systems. Dr. Camarero has authored over 120 peer-reviewed publications and secured substantial funding from NIH, DoD-CMDRP, American Cancer Society, Melanoma Research Alliance, and American Lung Association. His research has resulted in numerous patents for cyclotide-based therapeutics targeting various diseases including cancer, cardiovascular conditions, and autoimmune disorders. Recipient of NIH Big Idea Award for developing antibody substitutes Holds multiple patents related to cyclotide therapeutics Principal investigator on multiple NIH R01 and R35 grants Recipient of Melanoma Research Alliance Established Investigator Award Recipient of American Cancer Society Discovery Boost Grant His laboratory maintains active collaborations across USC and with industry partners including Bristol-Myers Squibb. Dr. Camarero's work has been featured in USC News and other media outlets highlighting his contributions to cancer treatment research and antimicrobial peptide development.

Ulrika KjellmanView profile

Associate Professor

• Archival Science
• Cultural Heritage
• Knowledge Organization
• +5 more

Ulrika Kjellman is a Senior Lecturer/Associate Professor at the Department of Literature, Media and Film (ALM) at Uppsala University. She is an active researcher in the fields of archival science, cultural heritage, and visual studies, with particular expertise in the intersection of documentation practices and race science history. Dr. Kjellman's research focuses on knowledge organization in Libraries, Archives, and Museums (LAMs), visual representation in scientific practices, and the ethical management of sensitive cultural heritage materials. Her work spans multiple disciplines including archival science , cultural heritage studies , visual epistemology , and critical race studies . She has made significant contributions to understanding how visual materials function as scientific documents, particularly in the context of historical race biology research. Her recent publications reveal a consistent focus on the role of visual materials in scientific documentation, particularly examining how photography and other visual representations were used in race biology practices. Her work also explores contemporary challenges in digital archiving, knowledge organization, and the ethical management of sensitive cultural heritage. A notable thread throughout her research is the examination of whiteness construction in scientific practices and the implications for contemporary archival and documentation work. Dr. Kjellman has collaborated with researchers across Scandinavia and internationally, contributing to edited volumes and interdisciplinary projects examining the impact of digitalization on cultural heritage institutions. Her research demonstrates a strong commitment to bridging theoretical frameworks with practical applications in archival and library science.

• Artificial Intelligence
• Data Science
• Health Informatics
• +3 more

Jorge Raul Navarro-Cabrera serves as a contracted lecturer in the Faculty of Engineering and Architecture at Peruvian Union University since March 2025, while concurrently holding technical and editorial roles at Universidad Nacional de San Martin in Tarapoto, Peru. His institutional affiliations demonstrate dual engagement in academic instruction and university publishing operations. He earned his Systems and Computer Engineering degree from Universidad Nacional de San Martin, establishing the foundation for his interdisciplinary research career. This educational background directly informs his applied technical approach across diverse domains. Navarro-Cabrera's research program centers on artificial intelligence and data science applications addressing Peruvian societal challenges. His work in health informatics develops non-invasive diagnostic tools using computer vision, while tourism technology research focuses on ICT solutions for destination promotion. Educational data mining constitutes another pillar, particularly unsupervised learning for student retention prediction. These threads converge in practical implementations like municipal sociocultural web applications and immigration risk classification systems. Analysis of his 15 most recent publications reveals a consistent pattern of collaborative research with Miguel Valles-Coral and Lloy Pinedo, spanning healthcare diagnostics, tourism innovation, and educational technology. The geographical focus remains predominantly Peruvian, with methodological strengths in unsupervised learning algorithms and multimodal data analysis. His academic service includes editorial assistance for scientific journals at Universidad Nacional de San Martin, complementing his technical role in the university's editorial department. This combination of teaching, research, and publishing support reflects a multifaceted academic profile engaged with both theoretical and operational aspects of higher education.