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Gargi BhaduriView profile

Associate Professor

• Sustainable Supply Chain Management
• Consumer Behavior
• Brand Transparency
• +5 more

Gargi Bhaduri is an Associate Professor and Associate Director of the School of Fashion at Kent State University's College of the Arts. She holds a Ph.D. in Human Environmental Sciences from the University of Missouri (2014), with a focus on Textile and Apparel Management. Her academic roles include teaching, research leadership, and program coordination in fashion merchandising. Education: Bachelor of Fashion Technology (Apparel Production), National Institute of Fashion Technology, India (2009) MS in Textile and Apparel Management, University of Missouri (2011) PhD in Human Environmental Sciences, University of Missouri (2014) Graduate Certificate in Center for Digital Globe, University of Missouri Research Interests: Empowering supply chain stakeholders through information transparency, sustainable consumption, brand communication strategies, and ethical apparel practices. She employs mixed-method approaches in studying consumer behavior related to sustainability, luxury goods, and corporate social responsibility. Awards and Recognition: Reviewer of the Year (2017), Clothing and Textiles Research Journal Most Cited Article (Sage Publishing) Marjorie Joseph Scholarship (2012) ITAA Fellowships (2010-2013) Service and Committees: Active contributor to the International Textile and Apparel Association (ITAA), serving on committees and receiving service awards. Engages in academic leadership roles within Kent State's School of Fashion. Labs/Initiatives: Involved in TechStyleLAB and fashion industry collaborations focused on sustainable practices and innovative education methods.

Bogumiła HnatkowskaView profile

Assistant Professor

• Software Engineering
• Analysis and Design of Information Systems
• Software Development Methodologies
• +3 more

Dr. Bogumiła Hnatkowska serves as Assistant Professor at the Institute of Informatics within the Faculty of Computer Science and Management at Wrocław University of Science and Technology. Her academic career spans software engineering research and education with emphasis on model-driven approaches and quality assurance methodologies. Her research interests include: Software Engineering Analysis and Design of Information Systems Software Development Methodologies Model-Based Software Development Domain-Specific Languages Software Quality Recent publications (2021-2025) reveal concentrated research in model-driven engineering, business rules processing, and ontology integration. Key trends involve textual specification languages for use-cases, automated test generation mechanisms, and formal transformations for ontologies – demonstrating consistent application of theoretical rigor to practical software development challenges across agile and model-based contexts. Scientific Awards: No scientific awards were mentioned in the provided text Dr. Hnatkowska has served as principal investigator for multiple State Committee for Scientific Research grants including UML extensions for multimedia systems (2000), real-time systems analysis (2005), and model-driven database design (2008). Her teaching portfolio includes Software Engineering, Software System Development, and Advanced Programming Techniques courses where she supervises team projects providing students with hands-on development experience. She actively participates in partner programs including Visual Paradigm's Academic Training Partner Program (providing UML/BPMN/agile tools) and IBM Academic Initiative, supporting her research in software engineering methodologies and educational tool development.

Stephen RamseyView profile

Associate Professor

• Computational Systems Biology
• Bioinformatics
• Precision Medicine
• +6 more

Stephen Ramsey, an Associate Professor at Oregon State University, holds dual appointments in the School of Electrical Engineering and Computer Science (College of Engineering) and the Department of Biomedical Sciences (Carlson College of Veterinary Medicine). With a PhD in Physics from the University of Maryland, his postdoctoral training in computational genomics at the University of Washington, and professional experience at the Institute for Systems Biology and Center for Infectious Disease Research, Ramsey bridges computational methods with biomedical applications. Education : Ph.D., Physics, University of Maryland; M.S., Physics, University of Maryland; Sc.B., Mathematical Physics, Brown University Ramsey specializes in computational systems biology , focusing on bioinformatics , biomedical knowledge graphs , and precision medicine . His research integrates machine learning , gene regulatory network modeling , and multi-omics data analysis to address challenges in rare disease diagnostics , drug monitoring , and inflammatory disease mechanisms . Current work includes AI-driven biomedical translation and electrochemical biosensor development for non-invasive diagnostics . Recent publications highlight knowledge graph applications in translational biomedicine , causal network inference in clinical-environmental data integration , and cross-species cancer transcriptomics . His team develops tools like RTX-KG2 and PloverDB to standardize biomedical data sharing and semantic reasoning . Scientific Awards : 2019 Zoetis Award (Carlson College of Veterinary Medicine) 2016 NSF CAREER Award 2016 PhRMA New Investigator Award 2010 NIH K25 Mentored Quantitative Research Award Ramsey advises in computational biology courses (CS 446/546) and contributes to biomedical AI through projects like mediKanren for rare disease diagnostics . His NSF-funded research explores gene expression noise and regulatory network dynamics , while NIH and PhRMA grants support his translational medicine initiatives. He leads the Ramsey Laboratory , which develops graph-based reasoning tools for biomedical data translation and multi-omics integration . The lab's work spans comparative oncology models, electrochemical biosensors , and knowledge graph infrastructure for clinical decision support .

• Data Governance
• Semantic Modeling
• Knowledge Graphs
• +5 more

Zaiwen Feng is a researcher actively contributing to data governance, semantic modeling, and causal inference. His work focuses on knowledge graphs, graph-based methods, and service-oriented architectures through collaborations with institutions like the University of Queensland and universities in China. Research Focus : Graph Differential Dependencies, Entity Resolution, Causal Effect Estimation, and Ontology Alignment Methodologies : Machine Learning, Variational Autoencoders, Prompt Engineering, and Semantic Retrieval Application Areas : Biomedical Data, Property Graph Recommendation, and Process Model Repositories Key trends in his publications include automated semantic modeling , neural approaches for entity resolution , and causal inference with graph structures . He frequently collaborates with researchers like Keqing He, Wolfgang Mayer, and Selasi Kwashie across conferences such as HPCC, BIBM, and WISE.

Jelle de VriesView profile

Associate Professor

• Operations Management
• Behavioral Operations
• Incentive Systems
• +3 more

Jelle de Vries is an Associate Professor of Operations Management at Rotterdam School of Management (RSM), Erasmus University. He focuses on behavioral characteristics in operational settings, publishing in top journals like the Journal of Operations Management (JOM) and Production and Operations Management (POM). He serves as an Associate Editor at JOM and previously worked as an Assistant Professor at VU University Amsterdam. He holds a PhD (cum laude) and MPhil from RSM. His research explores topics such as incentive systems, individual differences in operations, and customer behavior in service industries. Notable projects include studies on order-picking performance, restaurant analytics, and the impact of waiting times on revenue. In 2018, he received a VENI research grant for Behavioral Operations research. His doctoral work earned the Jo van Nunen award for best logistics-related PhD in the Netherlands. Education: PhD (cum laude), Rotterdam School of Management MPhil, Rotterdam School of Management Awards: Jo van Nunen award (2016) Jack Meredith Best Paper Award (2019) TRAIL2014 Best Student Paper Award (2014) His work bridges behavioral science with operational systems, emphasizing practical applications in logistics and service industries. Current research trends include analytics-driven decision-making and incentive design for operational efficiency.

• Ontology Engineering
• Knowledge Representation
• Natural Language Processing
• +4 more

Dr. C. Maria Keet is a Professor in the Department of Computer Science at the University of Cape Town, South Africa. With a PhD from the Free University of Bozen-Bolzano (2008), she has established herself as a leading researcher in ontology engineering and multilingual natural language processing, particularly for African languages. Her research interests span Ontology Engineering , Knowledge Representation , Natural Language Processing for African languages (especially isiZulu), Conceptual Data Modeling , and Temporal Data Modeling . She has developed significant frameworks for ontology modularization, competency questions, and multilingual knowledge representation. Her work bridges theoretical computer science with practical applications for linguistic diversity in Africa, addressing the critical need for technology that serves low-resourced languages. Her recent publications (2023-2025) reveal a strong focus on advancing ontology engineering methodologies, improving multilingual language processing capabilities, and developing tools for temporal data modeling. She has pioneered approaches for representing African languages in computational systems, with particular attention to noun classification, verb conjugation, and part-whole relations in Bantu languages. Dr. Keet has made substantial contributions to educational resources in her field, including her 2023 book The What and How of Modelling Information and Knowledge - From Mind Maps to Ontologies , which serves as a comprehensive guide to knowledge representation techniques. She actively supervises graduate students and has developed in-house tools specifically for ontology engineering education, demonstrating her commitment to advancing both research and teaching in her field.

• Empirical Educational Research
• Educational Psychology
• Reading Comprehension
• +2 more

Jacqueline Matthäi serves as a Scientific Associate and Research Assistant at the Chair of Empirical Educational Research within the Faculty of Human Sciences at Otto-Friedrich University Bamberg, working under Prof. Dr. Cordula Artelt since May 2007. Her academic role focuses on empirical investigations of reading comprehension processes and teacher assessment methodologies in educational contexts. Education: Master's degree in Educational Science with minors in French and African Studies (University of Leipzig, 2000-2005) General higher education entrance qualification (Gymnasium Humboldt-Schule Leipzig, 1999) Matthäi's research centers on the intersection of teacher knowledge, text comprehension demands, and assessment accuracy in reading literacy. Her work examines how educators identify text difficulty features, evaluate student comprehension, and implement strategic reading interventions—particularly in elementary and lower secondary settings. She investigates the relationship between teachers' knowledge bases and judgment accuracy, developing specialized instruments to measure pedagogical expertise in reading comprehension domains. Her scholarship bridges theoretical educational psychology with practical classroom assessment applications. Analysis of her 2008-2015 publications reveals consistent specialization in reading assessment instrumentation and teacher cognition. The research trajectory shows progressive refinement of measurement tools for teacher knowledge about text features, with increasing focus on specificity in assessment practices across school levels. Collaborative work with Artelt dominates her output, indicating sustained research partnership within Bamberg's empirical education framework. Methodologically, her studies combine experimental comprehension tasks with teacher judgment analysis to identify accuracy determinants in literacy assessment. Advising and Grants: No formal student supervision or grant funding details are documented in available materials. Laboratory Affiliations: Her work appears connected to Bamberg's UFF (probably "University Research Focus") and PsyCoach initiatives mentioned in departmental materials, though specific lab leadership isn't indicated.

Axel PolleresView profile

Professor

• Semantic Web
• Knowledge Engineering
• Data Management
• +12 more

Axel Polleres is a full professor in the area of 'Data and Knowledge Engineering' at the Vienna University of Economics and Business (WU Wien) and a faculty member at the Complexity Science Hub (CSH) in Vienna, a position he has held since January 2017. His work bridges academic research and real-world applications in semantic technologies, knowledge graphs, and data governance. His research interests lie at the intersection of semantic web technologies, knowledge engineering, and data management. Focused on querying and reasoning over ontologies, logic programming, and rule-based systems, he explores how structured data can be effectively managed, validated, and integrated—especially through standards like SPARQL and SHACL. His work extends to applications in open data, legal data, biomedical informatics, and socio-environmental challenges such as climate and public health. The most recent publications highlight a growing trend toward practical and societal applications of knowledge graphs, including climate risk assessment, crisis response, healthcare accessibility, and open data governance. These works combine technical rigor in semantic modeling with impactful real-world use cases, particularly in European and Austrian contexts. Axel Polleres has been actively involved in international standardization, notably as co-chair of the W3C SPARQL Working Group, and serves on the editorial boards of the Semantic Web Journal and Journal of Web Semantics . He has contributed to numerous European and national research projects and has published over 100 articles in top-tier journals and conferences. He advises and collaborates with researchers across disciplines and institutions, contributing to interdisciplinary teams working on complex societal challenges. His work is supported by significant research grants, though specific funding sources are not detailed in the provided text. He leads and participates in research groups focused on semantic technologies, knowledge graphs, and data-driven policy.

• Semantic Web
• Data Integration
• Ontology Matching
• +4 more

Dominique Ritze is a Research Fellow at the Data and Web Science Group of the University of Mannheim. Her research focuses on ontology alignment, semantic web technologies, linked open data integration, and knowledge organization systems. She collaborates with Prof. Dr. Christian Bizer and Prof. Dr. Kai Eckert on projects like InFoLiS II, aiming to advance data integration and semantic web applications. Education: MSc Computer Science (Diplom-Informatikerin) Research Interests: Dominique’s work bridges theoretical and applied aspects of semantic web technologies. Key areas include ontology evaluation frameworks, cross-domain data integration, and the development of tools for provenance tracking and data reuse. She has contributed to methodologies for aligning knowledge organization systems (KOS) and enhancing discovery systems with linked data. Publications Trends: Her articles from 2010-2015 emphasize ontology alignment (e.g., OAEI evaluations), semantic web applications, and data integration techniques. Notable contributions include the ICE-Map visualization for KOS evaluation and the Mannheim Search Join Engine for cross-website table integration. Awards: No scientific awards explicitly listed in the provided texts. Projects & Teams: Active in the Data and Web Science Group, leading projects on web table matching and semantic data integration. Collaborates with global research networks through initiatives like the Ontology Alignment Evaluation Initiative.

David Chaves-FragaView profile

Assistant Professor

• Knowledge Graphs
• Data Integration
• Semantic Web
• +4 more

David Chaves-Fraga is an Assistant Professor at Universidade de Santiago de Compostela (Spain), affiliated with CiTIUS (Center for Intelligent Technologies) and a research collaborator at KU Leuven's DTAI group. His expertise lies in Knowledge Graph Construction (KGC), focusing on declarative mapping rules, data integration, and semantic web technologies. He completed his PhD at Universidad Politécnica de Madrid in 2021, researching Knowledge Graph Construction from heterogeneous data sources. Education PhD in Artificial Intelligence, Universidad Politécnica de Madrid (2016–2021) Master in Artificial Intelligence, Universidad Politécnica de Madrid (2015–2016) Bachelor in Computer Science, Universidade de Santiago de Compostela (2011–2015) Research Interests Dr. Chaves-Fraga specializes in optimizing data integration systems using declarative rules (e.g., RML), scalable KG materialization, and benchmarking tools like KROWN. He emphasizes reproducibility and sustainability in KG creation, advocating for community-driven standards. His work bridges theory and practice, addressing challenges in real-world KG adoption. Contributions He co-chairs the W3C Knowledge Graph Construction Community Group, organizes workshops like KGC and Sem4Tra, and coordinates initiatives like Open Summer of Code. His tools (e.g., SDM-RDFizer, RMLdoc) are widely used in the semantic web community. Key themes include RDF-star generation, SHACL constraint extraction, and ontology-mapping interoperability.

Beatrice MarkhoffView profile

Professor

• Semantic Web
• Knowledge Engineering
• Semantic Interoperability
• +5 more

Beatrice Markhoff is a Professor of Computer Science (CNU 27) at the University of Tours , affiliated with the Faculty of Science and Technology (Blois site) and the Computer Science Department . She is a member of the UMR CNRS 7324 - CITERES - Archaeology and Territories Laboratory (CITERES-LAT) and the Maison des Sciences de l'Homme Val de Loire (MSH VdL) . Her research focuses on semantic interoperability , Web of data , knowledge representation , and knowledge extraction , with significant collaborations in cultural heritage disciplines . Doctorate in Computer Science, University of Franche-Comté (1995) HDR (Habilitation to Direct Research), François Rabelais University of Tours (2013) Her research themes include semantic interoperability, knowledge engineering, and data mining, with applications in cultural heritage. She co-created the International Workshop on Semantic Web for Cultural Heritage and co-edited special issues for the Semantic Web Journal and JOCCH . She leads projects like ANR SESAMES (2018-2023), H2020 ARIADNEplus (2019-2022), and H2020 4CH (2021-2023). Her academic contributions span XML data management, semantic web technologies, and functional programming. Key projects include carto4CH for cultural heritage mapping and OpenArchaeo for knowledge graph profiling. She has co-supervised PhD theses on topics like LOD querying and knowledge extraction from Wikidata .

Bo HuiView profile

Assistant Professor

• Data Mining
• Machine Learning
• Graph Neural Networks
• +6 more

Bo Hui is an Assistant Professor of Computer Science at The University of Tulsa's College of Engineering & Computer Science. He received his Ph.D. in Computer Science and Software Engineering from Auburn University in 2023 and earned his B.S. in Computer Science from Xi'an Jiaotong University in 2013. Prior to his Ph.D., he worked as a senior software engineer in the industry. Education: Ph.D., Computer Science and Technology, Auburn University, 2023 B.S., Computer Science and Technology, Xi'an Jiaotong University, 2013 Dr. Hui's research focuses on data mining and machine learning, particularly in designing machine learning methods for complex real-world data while addressing social concerns such as privacy in AI. His work spans multiple application domains including traffic prediction, social recommendation systems, and biological data analysis. He has made significant contributions to graph neural networks, knowledge graph unlearning, and federated learning systems. Dr. Hui's publication record demonstrates a strong focus on machine unlearning (the 'right to be forgotten' in AI models), graph neural networks, and traffic prediction systems. His work bridges theoretical machine learning with practical applications, with a growing emphasis on privacy-preserving AI techniques. He frequently publishes in top-tier venues including ICCV, ICLR, KDD, and AAAI. Awards and Honors: NSF award #2348177 for machine unlearning research AAAI student scholarship award Dr. Hui currently advises two Ph.D. students (Ruimeng Ye and Yang Xiao) who began their studies in Fall 2024. His research is supported by an NSF grant (#2348177) focused on machine unlearning. He has served as a reviewer for major conferences including ICLR, AAAI, KDD, CVPR, ACL, and EMNLP. His teaching includes Data Mining (2024 Spring) and Interaction Design (2023 Fall). His research group appears to focus on data mining and machine learning with applications to real-world problems requiring privacy-aware solutions.

• Neural Engineering
• Neural Prosthetics
• Brain Plasticity
• +7 more

Stephen Helms Tillery is a professor at Arizona State University (ASU), holding the Lincoln Chair in Neural Engineering and Ethics. He is affiliated with the School of Biological and Health Systems Engineering and the Lincoln Center for Applied Ethics. His research focuses on neural mechanisms underlying sensorimotor control, particularly how the brain integrates sensory inputs to guide movement. He also leads ethical discussions on aligning research with societal benefit. Education: B.S. in Psychology (ASU), neuroscience studies at University of Minnesota (under John Soechting and Tim Ebner), postdoctoral work at SUNY Syracuse (under Peter Strick), and neuroprosthetics research at ASU with Andrew Schwartz. Research interests include brain plasticity, cortical neurophysiology, and neural prosthetics. His work combines human and nonhuman primate studies, with contributions to tactile feedback systems, cortical mapping, and neuroethical frameworks for translational research. Key research trends in his articles emphasize sensory integration, neuroprosthetic design, and ethical considerations in neural engineering. He has developed novel methods for non-invasive cortical mapping and advanced haptic feedback systems for prosthetics. He participates in the Global Futures initiative as a Senior Global Futures Scientist, addressing long-term societal impacts of neuroscience research. His work bridges technical innovation with ethical responsibility, ensuring technologies benefit broader communities.

Yuan AnView profile

Associate Professor

• Health Informatics
• Biomedical Information Systems
• Semantic Web
• +6 more

Dr. Yuan An is an Associate Professor and Director of International Programs at the College of Computing & Informatics, Drexel University. His research focuses on health and biomedical information integration, semantic-ontology mapping, and knowledge representation. Education: PhD in Computer Science, University of Toronto Master of Computer Science, Dalhousie University Master of Engineering in Systems Engineering, Tsinghua University Bachelor of Engineering, Tsinghua University Research Interests include conceptual modeling, schema and ontology mapping, information integration, healthcare systems, and semantic web technologies. His work bridges data science and healthcare informatics, with a focus on structured database design and case-based schema development. Selected Publications highlight his contributions to automated coding for occupational epidemiology, EMR error detection, and semantic mapping in biomedical contexts. His projects span data quality in medical records, big data analytics, and biological network mining. Scientific Awards & Grants NSF IU/CRC CVDI Center ($98,000, PI, 2013-2014) NSF I/UCRC Phase I ($275,000, Co-PI, 2012-2017) Best Student Paper Award at IEEE BIBM 2013 Precarn Scholarship (2004-2005) Professional Activities include service on program committees for IEEE BIBM, CIKM, and ACM conferences, as well as leadership in international academic initiatives.

Abhisekh Ghosh MoulickView profile

Assistant Professor

• Entrepreneurship
• Strategy
• Entrepreneurial Strategy
• +3 more

Abhisekh Ghosh Moulick is an active Assistant Professor in the Lawrence N. Field Department of Entrepreneurship and Innovation at the Zicklin School of Business, City University of New York (CUNY), with contact email Abhisekh.GhoshMoulick@baruch.cuny.edu and phone (646) 312-3635. His academic qualifications are: PhD from Texas A&M University BSc from University of London Research expertise centers on entrepreneurship and strategic management, with specialized focus on: Entrepreneurial Strategy Social Innovation and Entrepreneurship Nonmarket Strategy Strategic Human Capital United Way systems analysis Cross-cultural entrepreneurial experiences His work addresses institutional gaps in emerging economies and compensation dynamics in mission-driven organizations. Publication trends (2014-2023) reveal concentrated scholarship in causal complexity within entrepreneurship research, fiscal management in public schools, and United Way grant allocation systems. Key patterns include quantitative analysis of entrepreneurial phenomena, strategic compensation in nonprofits, and the impact of weak institutions on entrepreneurial catalysis. No scientific awards or honors were documented in the provided text. Student advising and grant activities are unreported; the text contains no references to doctoral students, master's candidates, or funded research projects. Institutional affiliations and research teams remain unspecified beyond his departmental appointment.