جست‌وجوی استاد و پژوهشگر

Diego Calvaneseمشاهده پروفایل

استاد مهمان

• Artificial Intelligence for Data Management
• Knowledge Representation and Reasoning
• Virtual Knowledge Graphs
• +۵ مورد دیگر

Diego Calvanese is a Visiting Professor at Umeå University's Department of Computing Science and holds a full professorship at the Free University of Bozen-Bolzano, Italy. His research focuses on AI for data management, including virtual knowledge graphs (VKG), ontology-based data access (OBDA), and formal methods like description logics. He is part-time at Umeå, balancing roles with his primary position in Italy. Calvanese has received prestigious awards including the AAAI Classic Paper Award (2021), EurAI Fellow (2015), and ACM Fellow (2019). He supervises three doctoral students at Umeå and has authored over 350 publications, with an h-index of 71. His work emphasizes data integration, geospatial systems, and ethical AI applications. Key Roles: Associate Programme Chair (IJCAI 2025), Programme Chair (IJCAI-ECAI 2026), Head of AI for Data Management Research Group Research Interests: Knowledge representation, graph data management, explainable AI, and telemonitoring systems like reCOVeryaID. His research group develops tools like Ontop, a VKG system enabling seamless data access across heterogeneous sources. Current projects include geospatial data integration and temporal OBDA frameworks. Calvanese has served on over 150 program committees and editorial boards, including Artificial Intelligence and JAIR. His work bridges technical advancements with societal impacts, addressing AI's role in healthcare, climate, and democracy.

David Wai-lok Cheungمشاهده پروفایل

استاد

• Database Systems
• Data Mining
• E-commerce Technologies
• +۵ مورد دیگر

Professor David Wai-lok Cheung is a Professor in the Department of Computer Science at the University of Hong Kong (HKU) and Director of the Center for E-commerce Infrastructure Development (CECID). He holds a BSc in Mathematics from the Chinese University of Hong Kong and MSc/PhD in Computer Science from Simon Fraser University, Canada. His research focuses on database systems, data mining, e-commerce technologies, and secure computation. Key contributions include pioneering work on privacy-preserving data mining, XML schema design, and e-commerce infrastructure development. He has led numerous prestigious grants totaling over HK$60M and developed widely adopted open-source tools like the ebXML gateway. Professor Cheung has received awards such as the HKU Outstanding Researcher Award (1999) and the Distinguished Contribution Award (2009 PAKDD). He actively contributes to academia through leadership roles in conferences like PAKDD and CIKM. His research spans secure computation, data interoperability, and bioinformatics, with over 150 publications in top venues like SIGMOD, VLDB, and KDD. **Grants & Funding**: Highlighted grants include HK$6.6M for eLogistics Appliance (2007-2008) and HK$9.198M for a service-oriented e-transaction platform (2006-2008). **Publications**: Over 150 papers in areas like privacy-preserving data mining, XML query processing, and spatiotemporal data analysis. **Service**: Member of RGC Engineering Panel, Hong Kong Deposit Protection Scheme board, and Certification Board for IT Professional Certification.

Ralph Peetersمشاهده پروفایل

پژوهشگر

• Entity Matching
• Data Integration
• Large Language Models
• +۳ مورد دیگر

Ralph Peeters is a Postdoctoral Researcher at the Data and Web Science Group within the University of Mannheim . He specializes in entity matching, data integration, and web-based systems. His research explores the application of large language models and deep learning techniques to improve product matching and knowledge graph construction. Focus areas: Entity Matching, Data Integration, Large Language Models Teaching roles: Course Creator/Lecturer for LLM-based Agents, TA for Data Mining, Web Mining, and Web Data Integration (2019–2025) Collaboration: Works under the supervision of Prof. Dr. Christian Bizer Recent publications highlight his work on benchmarks like WDC products and SOTAB, which leverage schema.org annotations and semantic web technologies for improving data quality and integration at scale. His research combines traditional NLP techniques with modern deep learning approaches.

Yaser Oulabiمشاهده پروفایل

پژوهشگر

• Knowledge Base Completion
• Web Data Integration
• Entity Extraction
• +۳ مورد دیگر

Yaser Oulabi is a researcher at the University of Mannheim's Chair of Information Systems V: Web-based Systems. His work focuses on knowledge base augmentation through web data extraction, particularly developing methods to integrate long-tail entities from web tables into cross-domain knowledge graphs like DBpedia and Wikidata. Key contributions include creating the Time-Dependent Ground-Truth Dataset for evaluating temporal data fusion and curating the Web Tables for Long-Tail Entity Extraction benchmark. His research addresses challenges in entity resolution for sparse datasets, temporal metadata estimation using knowledge-based trust metrics, and weak supervision approaches for identifying rare entities. Dr. Oulabi's frameworks enable structured web data consolidation across domains through innovative conflict resolution and version management techniques. Recent publications examine how web table characteristics influence knowledge base expansion potential and develop data programming methods for entity extraction in low-resource domains.

Anna Primpeliمشاهده پروفایل

پژوهشگر

• Data Extraction
• Data Integration
• Entity Matching
• +۴ مورد دیگر

Dr. Anna Primpeli is an Alumni Researcher at the University of Mannheim's Data and Web Science Group within the School of Business Informatics and Mathematics . Her research focuses on data extraction, integration, and entity matching, with particular emphasis on leveraging active learning and semantic web technologies. She contributes to large-scale benchmark datasets such as the Web Data Commons series, which provide foundational resources for entity resolution and data mining. Her work often intersects with practical applications in product data integration and web-scale data analysis. Teaching contributions include courses on Web Mining , Data Mining , and Large-Scale Data Integration , reflecting her expertise in both theoretical and applied aspects of data science. Key research trends in her publications include improving entity matching through active learning techniques, developing robust benchmarking frameworks, and utilizing schema.org annotations for scalable data integration. She has collaborated extensively with colleagues like Christian Bizer and contributed to initiatives like the MWPD2020 Semantic Web Challenge.

Sören Auerمشاهده پروفایل

استاد

• Semantic Technologies
• Knowledge Engineering
• Data Science
• +۷ مورد دیگر

Prof. Sören Auer is the Director of the German National Library of Science and Technology (TIB) and Professor of Data Science and Digital Libraries at Leibniz Universität Hannover's Faculty of Electrical Engineering and Computer Science . With academic positions at Dresden, Yekaterinburg, Leipzig, Pennsylvania, Bonn, and Fraunhofer Society, his career focuses on semantic technologies , knowledge engineering , and Artificial Intelligence Research Data Management Open Science Knowledge Graphs . He leads the Open Research Knowledge Graph (ORKG) initiative and co-founded DBpedia and eccenca.com . His research spans data science , AI-driven knowledge representation , and digital library systems . He has supervised numerous PhD theses and final-year theses while offering courses on Knowledge Engineering Semantic Web Technologies Data Integration Scientific Data Management . The technical focus includes semantic data interlinking , neuro-symbolic AI , and contextual metadata frameworks . As a recipient of prestigious awards including ERC Consolidator Grant SWSA Ten-Year Award ESWC 7-Year Best Paper Award OpenCourseware Innovation Award , Prof. Auer has led major projects like BigDataEurope and contributes to standards in W3C , NFDI , and EOSC . His recent publications demonstrate advancements in ontology alignment , LLM-driven schema discovery , and hybrid AI systems for scholarly knowledge organization.

Monika Lanzenbergerمشاهده پروفایل

استادیار

• Semantic Web
• Ontology Alignment
• Information Visualization
• +۴ مورد دیگر

Monika Lanzenberger is an Assistant Professor at the Institute of Software Technology and Interactive Systems, Faculty of Informatics, Vienna University of Technology. Her research focuses on the intersection of Semantic Web technologies, ontology alignment, and information visualization. She has established herself as a notable researcher in visual ontology alignment through her development of the AlViz tool and related publications. Dr. Lanzenberger received her PhD from the Vienna University of Technology, Faculty of Informatics in 2003 and her MSc in Computer Science from the same institution in 2001. She completed a Post-Doc Fellowship (ERCIM) with the NTNU, Department of Computer and Information Science, Trondheim, Norway (February - October 2005) and with the Centre for IT Innovation (CITI) at the CRP Henri Tudor, Luxembourg (November 2005 - July 2006). Her primary research interests center around Semantic Web and Ontology-based Data, with specific focus on ontology alignment and visualization techniques. She has made significant contributions to the field through her work on visual ontology alignment tools, particularly the AlViz system. Her research also extends to Human Computer Interaction, Information Visualization techniques, feminist perspectives on computer science, and online learning and didactics. She has published extensively in top conferences and journals in these areas, with a particular emphasis on making ontology alignment more accessible through visualization. Dr. Lanzenberger has received recognition for her work, including an Outstanding Paper Award in 2002 for her research on the evaluation of navigation in hypertext learning systems. She is an active member of the scientific community, serving as a reviewer for international conferences and co-organizer of workshops in her field. As an educator, Dr. Lanzenberger has taught numerous courses including Information Visualization, Women in Science and Technology, Fundamentals of Methodical Working, and Semi-Automatic Information and Knowledge Systems. She has supervised multiple student projects, Bachelor's theses, and Master's theses, particularly in areas related to information visualization and semantic technologies. She is a member of several professional organizations including IEEE, ÖGAI, OCG, and GI, demonstrating her active engagement with the broader computer science community.

Howard Berenbaumمشاهده پروفایل

استاد

• Psychopathology
• Emotional Processes
• Emotional Awareness
• +۳ مورد دیگر

Howard Berenbaum is a Professor of Psychology at the University of Illinois, affiliated with the Center for Social & Behavioral Science. His research focuses on explaining adult psychopathology through emotional processes, emphasizing disturbances in emotional valence, intensity, regulation, and awareness. He holds a Ph.D. from Indiana University Bloomington. Key research areas include emotional awareness, meta-emotion factors, and the interplay between emotions and psychological disorders such as schizophrenia and autism spectrum conditions. Recent work explores misophonia, pleasurable emotions, and cross-cultural psychological phenomena. His studies utilize experimental paradigms and interdisciplinary collaborations, with findings published in journals like *Journal of Positive Psychology* and *Schizophrenia Research*. His work demonstrates a focus on translational research, aiming to bridge theoretical insights with clinical applications. Notable contributions include frameworks for categorizing emotional disturbances and examining the role of cultural and individual differences in psychopathology. Berenbaum’s research has been cited widely, influencing debates on emotion regulation, trauma, and cognitive-behavioral interventions. He has collaborated internationally, including studies comparing American and Chinese young adults, and has investigated comorbidities like misophonia and hearing disorders. His grants and lab activities are centered on advancing understanding of emotion’s role in mental health, with a particular interest in veterans’ psychological challenges and developmental pathways to psychopathology.

• Translation Technologies
• Machine Translation
• Post-editing Evaluation
• +۴ مورد دیگر

Mihaela Vela is a Senior Lecturer at the Department of Language Science and Technology at Saarland University. Her research focuses on machine translation evaluation, post-editing strategies, and translation technologies. Prior to her academic role, she worked as a researcher at the Language Technology Lab of DFKI (2007–2011), contributing to projects like ontology schema extraction from financial news. She holds a PhD in Computational Linguistics (2011) from Saarland University, supervised by Hans Uszkoreit and Thierry Declerck, and a Licentiate degree in Linguistics from West University of Timisoara. Her teaching portfolio includes courses such as Translation and Content Management , Applied Language Technologies , and Machine Translation , reflecting her expertise in integrating computational methods with translation practice. She has developed tools like TeLeMaCo (a collaborative teaching repository) and Catalog (a post-editing interface). Her work emphasizes improving translation workflows through better CAT tool design, metadata preservation, and cognitive load analysis in post-editing tasks. Key contributions include the SubCo corpus of learner translations and studies on post-editing effort in low-resource languages. Her research bridges theoretical linguistics with practical applications, addressing challenges in legal text classification, parliamentary discourse analysis, and neural post-editing systems.

• Database Systems
• Semantic Heterogeneity
• Federated Databases
• +۳ مورد دیگر

Dennis McLeod is a Professor at the University of Southern California , specializing in Database Systems , Ontology Engineering , and Semantic Heterogeneity resolution. His work bridges Federated Database Systems and Web Engineering , focusing on component-based architectures, adaptive ontologies, and geospatial data processing. Key Research Areas : Semantic heterogeneity, ontology-driven data mining, mobile web information management, and distributed systems. Collaborations : Extensive partnerships with researchers like Qing Li , Cyrus Shahabi , and Stefania Leone across institutions. Publications (2014-1995) span topics from component-based web engineering to distributed earthquake science , with recent work on geostreaming, social network tag-geotag analysis, and spam filtering using ontologies. His contributions include frameworks for multi-resolution document transmission , object-oriented database sharing , and adaptive query optimization in federated systems. Scientific Impact : Co-chairs and tutorials at major conferences (VLDB, CoopIS, ICDE). Co-edited proceedings for ICWL 2008 and contributed to Expert Database Systems (1989-1991). Pioneered INTERBASE for controlled sharing in federated databases (1990).

Antoon Bronselaerمشاهده پروفایل

استادیار

• Data Quality
• Data Fusion
• Uncertainty Management
• +۲ مورد دیگر

Antoon Bronselaer is an Assistant Professor at Ghent University's Department of Telecommunications and Information Processing within the Faculty of Engineering and Architecture. He is an active member of the Database, Document and Content Management (DDCM) research group, focusing on advancing database theory and applications. His research centers on data quality (particularly measurement models and improvement techniques), temporal databases , data fusion , and uncertainty management in databases . Key contributions include measure-theoretic foundations for data quality assessment, dynamical order construction in data fusion, and predicate enrichment techniques for wrapper induction. Analysis of his recent publications reveals consistent innovation in data cleaning algorithms (e.g., Swipe framework), temporal data modeling, and orthographic similarity measures for graph-based text representations. His work increasingly bridges database theory with healthcare applications (e.g., statin-gait relationship studies) and digital humanities (Byzantine epigrams project). No scientific awards are mentioned in the source materials. Dr. Bronselaer's academic guidance includes formal advisees at Ghent University, though specific student names aren't documented in the provided texts. His research is supported through university positions and likely Belgian/Flemish research grants given his publication venues. Current projects involve automated news update analysis, persistent identifier validation, and syntactic interoperability frameworks. He leads research within the DDCM group, specializing in data quality measurement systems and temporal data management solutions. Recent work demonstrates expansion into healthcare data analytics and cultural heritage informatics while maintaining core expertise in database theory.

Theodoridis Ioannisمشاهده پروفایل

استاد

• Data Science
• Databases
• Big Data Management
• +۳ مورد دیگر

Professor Theodoridis Ioannis is a distinguished faculty member in the Department of Informatics at the University of Piraeus, where he serves as Director of the Data Science Laboratory within the School of Information and Communication Technologies. With a career spanning over two decades, he has established himself as a leading expert in data management and analysis. His research interests focus on Data Science, particularly in databases, big data management, data mining, and geoinformatics. Professor Theodoridis has made significant contributions to spatial database systems, time series analysis, and distributed data processing. His work bridges theoretical foundations with practical applications in areas such as smart cities, mobility analytics, and scientific data management. His publication record demonstrates consistent research productivity with over 100 peer-reviewed articles in top-tier venues, accumulating more than 10,000 citations. His research output shows a clear evolution from foundational database techniques toward contemporary challenges in big data analytics, machine learning integration, and privacy-preserving methods. Member of editorial board of ACM Computing Surveys (since 2016) Reviewer for numerous international journals and conferences Active participant in data management conference committees Professor Theodoridis has secured significant research funding through Horizon 2020 projects, serving as project coordinator and research team leader since 2001. His work demonstrates strong industry and academic collaboration, with applications spanning multiple domains. He has also co-authored three influential monographs in his field. He leads the Data Science Laboratory, which serves as a hub for interdisciplinary research at the intersection of database systems, machine learning, and domain-specific applications. The laboratory fosters collaboration between computer scientists, domain experts, and industry partners to address real-world data challenges.

• Data Integration
• Machine Learning
• Schema Matching
• +۵ مورد دیگر

C. Koutras is a researcher at the Data-Intensive Systems group within the School of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His work focuses on data integration, schema matching, and machine learning applications in modern data systems. Research Areas: Data Integration, Schema Matching, Machine Learning, Data Lakes, Graph Neural Networks, Biomedical Data Systems Collaborations: Active collaborations with researchers including R. Hai, A. Katsifodimos, and M. Jarke. Recent work includes developing tools like Amalur and Valentine , which address challenges in data lake integration and scalable schema matching. His research leverages large language models and graph-based techniques for biomedical and distributed data environments. Despite significant contributions to data integration and machine learning, no explicit scientific awards or part-time status are documented in the provided materials. His 2024 dissertation at TU Delft highlights expertise in modern data challenges.

• Information Extraction
• Natural Language Processing
• Data Privacy
• +۳ مورد دیگر

Besat Kassaie is a Postdoctoral Researcher collaborating with Renée Miller. His research focuses on information extraction, natural language processing, and data privacy. Key areas include improving unstructured data quality through updatable extracted views, mathematical information retrieval (MathIR), and ontology matching techniques. His work spans theoretical advancements in information systems and practical applications in healthcare analytics. Notable contributions include frameworks for automated view maintenance, differential privacy methods for text data, and systems for detecting math answers using neural networks like Tangent-L. Kassaie's articles demonstrate a strong emphasis on database systems optimization, dynamic data processing, and the intersection of AI with mathematical problem-solving. His research bridges foundational computer science principles with real-world challenges in data privacy and interpretability.

• Business Processes
• Blockchain Technology
• Semantic Technologies
• +۵ مورد دیگر

Assoc. Prof. Julius Köpke is an Associate Professor at the University of Klagenfurt's Department of Informatics Systems. His research focuses on business processes, blockchain technology, and semantic interoperability, with particular emphasis on smart contracts, artifact-centric processes, and interorganizational systems. He is affiliated with the Information and Communication Systems research group and contributes to the Institute for Computer Science Systems. Research Interests: - Interorganizational business processes with a focus on blockchain and smart contracts - Application of semantic technologies for data interoperability - Artifact-centric process modeling and data provenance Key Contributions: - Developed SecBPMN2BC framework for secure blockchain-based process modeling - Authored methods for aligning global and local processes, optimizing data-flow implementations - Pioneered lightweight XML-Schema annotation techniques for data translation Recent Work: - Explored LLM-based conversational process modeling tools - Investigated blockchain channel storage for business process data - Published extensively on time-aware processes and temporal constraints Labs/Teams: - Member of the Information and Communication Systems team - Active contributor to the Department of Informatics Systems' research initiatives