جست‌وجوی استاد و پژوهشگر

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.

Josef Ruppenhoferمشاهده پروفایل

پژوهشگر

• Natural Language Processing for Educational Applications
• Corpus Linguistics
• Frame Semantics
• +۳ مورد دیگر

Josef Ruppenhofer is a computational linguist working as a Researcher at FernUniversität in Hagen, where he contributes to the CATALPA research cluster. Since March 2023, he has served as a Research Assistant at the research professorship for Computational Linguistics in the DAKODA project, which focuses on applying NLP methods to study second language acquisition. His work bridges theoretical linguistics with practical applications in language education technology. Dr. Ruppenhofer earned his PhD in Linguistics from the University of California at Berkeley in 2004, following MA degrees from UC Berkeley (1999) and the University of Colorado at Boulder (1997). His academic journey includes postdoctoral positions at prestigious institutions including the International Computer Science Institute in Berkeley, Saarland University, Hildesheim University, and the Leibniz-Institute for the German Language. Ruppenhofer's research centers on applying computational methods to linguistic phenomena, with particular expertise in frame semantics, construction grammar, and corpus linguistics. His work spans educational applications of NLP, sentiment analysis, and the challenging domain of offensive language detection. He has developed innovative approaches for analyzing learner language corpora and identifying implicit forms of abusive language that deviate from social norms. Analysis of his recent publications reveals a consistent focus on the intersection of theoretical linguistics and practical language technology applications. His work shows increasing specialization in analyzing implicit forms of abusive language and developing methods for operationalizing developmental stages in second language acquisition, particularly for German as a foreign language. The DAKODA project represents a major focus of his current research trajectory. Ruppenhofer actively contributes to the computational linguistics community through his work on FrameNet (celebrating its 25th anniversary in his 2024 publications) and the development of linguistic resources for analyzing user-generated content and parliamentary discourse. His methodological approach consistently combines theoretical linguistic insights with practical computational techniques. As a member of the CATALPA research cluster, Ruppenhofer collaborates with an interdisciplinary team working at the intersection of language education, theoretical linguistics, and computational methods. His current work in the DAKODA project involves building tools and methodologies for analyzing learner corpora to better understand developmental stages in second language acquisition.

• Innovation Economics
• Competition Economics
• Privacy Policies
• +۳ مورد دیگر

Bernhard Ganglmair is an Associate Professor of Economics at the University of Mannheim and Head of the Junior Research Group 'Competition and Innovation' at ZEW (Leibniz Centre for European Economic Research). His roles include membership in the board of the Mannheim Centre for Competition and Innovation (MaCCI) and the steering group of the Competition Law and Economics European Network (CLEEN). He holds editorial positions at the International Journal of Industrial Organization and Economic Inquiry. Education: PhD in Economics from the University of Zurich (2011) Master's degree in Economics from the University of Linz Research Interests: Ganglmair's work focuses on innovation economics, competition policy, privacy policies, and contract theory. He employs both theoretical and empirical methods, including text-as-data approaches, to study topics like strategic information disclosure, technology standardization, and regulatory compliance. His research often bridges law and economics, examining how institutional frameworks influence market behavior and innovation outcomes. Grants and Projects: He leads projects funded by the DFG Collaborative Research Center Transregio 224 (EPoS) and the Women & Science Chair at Université Paris Dauphine - PSL. Recent work includes analyzing German privacy policy compliance, gender diversity in technology standardization, and patent claim dynamics. Labs and Activities: Ganglmair organizes workshops like the Disclosure, Information Sharing, and Secrecy (DISS) Conference and contributes to initiatives such as the MaCCI IO Day. He has held visiting positions at institutions like the University of Bologna and Boston University.

Andreas Harthمشاهده پروفایل

استاد

• Semantic Web
• Linked Data
• Knowledge Graphs
• +۸ مورد دیگر

Prof. Dr. Andreas Harth (born 1976) is a leading researcher in decentralized information systems and data portability, holding the Chair of Business Information Systems at Friedrich-Alexander-Universität Erlangen-Nürnberg while heading the Data Spaces and IoT Solutions department at Fraunhofer IIS. His work bridges Semantic Web technologies with industrial IoT applications, focusing on making enterprise data context-independent. Research areas: Semantic Web, Linked Data, Knowledge Graphs, IoT, Industry 4.0 Key projects: i-VISION, ARVIDA, PlanetData, MEREGIOmobil Academic background: PhD from Digital Enterprise Research Institute (2010), Karlsruhe Institute of Technology habilitation (2016) Former affiliations: Stanford University, University of Southern California, University of Heidelberg Harth's research emphasizes data integration through formal logic and graph-based representations, enabling companies to merge shipment data with commercial records or optimize warehouse processes using RFID and near-field detection. His 2019-2023 publications reveal a trend toward entity-centric data fusion and real-time workflow execution in dynamic environments. He advocates cloud alternatives like Nextcloud for SME data sovereignty and explores Solid technology for decentralized data control. Scientific Contributions: Co-developer of YARS2 federated query framework (2007) Key figure in JPEG XS ISO standard development (2025 Joseph von Fraunhofer Prize) Lead architect of FusE data fusion system (ACM Transactions, 2019) Primary investigator in multiple EU research initiatives (PlanetData, NeOn) Harth actively consults with manufacturing companies through Fraunhofer IIS' Supply Chain Services division, applying rapid IoT prototyping for cost-effective digitalization. He leads the Semantic Web Lab, creating machine-readable workflow models for industrial applications.

Mikhail Polianskiiمشاهده پروفایل

پژوهشگر

• Russian Foreign Policy
• European Security
• NATO Relations
• +۳ مورد دیگر

Dr. Mikhail Polianskii is a Postdoctoral Researcher at Leibniz Institute Peace Research Institute Frankfurt (PRIF) since 2024, working under the PATTERN project on Russian foreign policy and European security. His research spans nuclear arms control, hybrid warfare, and crisis management in geostrategic contexts. Education : B.A. and M.A. in International Relations (Voronezh State University, MGIMO), Ph.D. in Political Science (University of Frankfurt, 2019–2024) Professional Background : Visiting Fellow at National Research University Higher School of Economics (Moscow, 2021), Research Associate at PRIF (2019–2023) His work focuses on Russian-Western relations, analyzing dissociation from Pan-European security frameworks and Cold War lessons for modern conflicts. Recent publications examine nuclear deterrence post-Ukraine, Russia-China strategic alignment, and institutional collapse in security orders. Scientific Awards : Johanna-Quandt-Scholarship (2021) National Essay-Contest Winner 'Russia, Europe, World' (2020) Egon Bahr Fellowship (2019) He engages in policy advice for US Senate Committee on Intelligence, Consulate General of Japan, and Korean diplomatic entities, while contributing to media outlets like Handelsblatt, France24, and Frankfurter Rundschau.

Ziawasch Abedjanمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Database Systems
• +۵ مورد دیگر

Ziawasch Abedjan is a full professor of computer science and chair of the Data Integration and Data Preparation (D2IP Lab) Group at Technische Universität Berlin, part of the Berlin Institute for the Foundations of Learning and Data (BIFOLD). He holds a PhD from the Hasso Plattner Institute (2014) and was previously a junior professor at TU Berlin (2016–2020), with postdoctoral work at MIT (2014–2016). His research focuses on scalable methods for processing large heterogeneous datasets, emphasizing automated data preparation, extraction, and cleaning for data science workflows. Education: PhD in Computer Science, Hasso Plattner Institute (2014) MSc in Computer Science, Hasso Plattner Institute (2010) BSc in Computer Science, Hasso Plattner Institute (2008) Research Interests: Dr. Abedjan’s work bridges database systems and machine learning, addressing challenges in data integration, automated data cleaning, and scalable data science tools. His team develops systems like Blend for unified data discovery and MATE for multi-attribute table extraction. Recent projects include exploring the environmental impact of AutoML and advancing catalog enrichment techniques. Awards & Recognition: First Prize, GI Data Science Challenge (BTW 2023) SIGMOD Reproducibility Award (2019) Best Dissertation Award (2013/2014) Teaching & Service: Teaches foundational courses in data structures and databases. Serves on committees for major conferences (SIGMOD, VLDB) and chairs roles such as Reproducibility Chair for BTW (2023/2025). Active in editorial roles for journals including ACM JDIQ and IEEE Data Engineering Bulletin. Labs & Teams: Leads the D2IP Lab, collaborating with universities and industry. Current projects include TDC2 NFDI4DS. Offers thesis topics in data science lifecycle optimization and ML system design.

Ansgar Scherpمشاهده پروفایل

استاد

• Data Science
• Big Data Analytics
• Text Analytics
• +۷ مورد دیگر

Professor Ansgar Scherp is a leading academic in Data Science and Big Data Analytics at Ulm University , Germany. His career spans multiple institutions including University of Essex, University of Stirling, and Kiel University, where he led the EU Horizon 2020 MOVING project. He holds a habilitation thesis on Semantic Media Management and has pioneered research in combining symbolic and statistical methods for data analysis. Current: Professor for Data Science & Big Data Analytics (Ulm University) Previous: Professor for Knowledge Discovery (Kiel University), Juniorprofessor roles (Mannheim, Koblenz-Landau) Skills: Semantic Web, Graph Mining, Text Analytics, Multimedia Systems His research interests focus on integrating Information Retrieval, Data Mining, Machine Learning, and Semantic Web technologies. He has developed innovative methods like HCF-IDF for semantic profiling and SchemEX for schema-level indexing of Linked Data. His work addresses challenges in media companies' digital transformation and large-scale Knowledge Graph analysis. Scientific awards include: Best Paper Award, Symposium on Document Engineering (2021) Best Student Paper Award, Symposium on Document Engineering (2019) ACM SIGMM Rising Stars Symposium Speaker (2016) Double Winner of Billion Triple Challenge (2008, 2011) klickTel Award (2013) He has supervised 12 PhD theses and over 15 Master's theses , with students now working at Google, Capgemini, and academic institutions. His email addresses are ansgar.scherp@uni-ulm.de and mail@ansgarscherp.net .

• Corporate and Capital Market Law
• Banking Law
• Contract Law
• +۴ مورد دیگر

Prof. Dr. Florian Möslein holds the Chair of German Civil Law and German and European Business Law at Philipps-Universität Marburg, where he leads research at the Institut für das Recht der Digitalisierung (IRDi). His work bridges the Institute for Commercial, Business and Labor Law and cutting-edge digital regulation studies. Research focuses on: Innovation/digitalization in contract law, corporate structures, and financial systems Corporate social responsibility frameworks and sustainability certification Rulemaking theory exploring regulatory design and economic analysis Recent publications demonstrate strong emphasis on digital transformation impacts across corporate governance, financial regulation, and contractual frameworks, with increasing attention to AI, blockchain, and platform economies.

Lukas Laskowskiمشاهده پروفایل

پژوهشگر

• Data Matching
• Data Integration
• Ontology Learning
• +۳ مورد دیگر

Lukas Laskowski is a researcher at the Hasso Plattner Institute (HPI) in Potsdam, Germany, affiliated with the Information Systems Group under Prof. Felix Naumann. His work bridges database systems, machine learning, and real-world applications, with publications in premier venues including SIGMOD, NeurIPS, and BTW. He maintains an active research profile with multiple forthcoming publications through 2026. His research concentrates on data matching and integration , where he pioneers explainable methods and active learning frameworks. He significantly contributes to ontology learning from relational databases through benchmark development and explores event sequence modeling with mixed data types. His interdisciplinary work extends to computer vision for ecological conservation, specifically developing open-set re-identification systems for wildlife monitoring in natural habitats. Analysis of his publication trajectory (2022-2026) reveals a cohesive evolution from foundational platform development (Frost) to sophisticated benchmarking (Burr) and explainability in data matching. His research increasingly integrates machine learning with database systems to address data quality challenges for AI applications, while maintaining strong connections to ecological and biomedical domains through projects like GorillaVision. Scientific Awards: No awards listed in available information Advising and Grants: No specific information regarding advised students or secured grants appears in the provided materials, though he participates in master's thesis supervision through group activities. Labs and Teams: Laskowski operates within the Information Systems Group at HPI, contributing to major initiatives including Metanome (large-scale data profiling), KITQAR (data quality for AI applications), and Metis (data quality assessment). The group emphasizes open-source tool development, reproducibility, and cross-institutional collaboration in data management research.

Wouter Beekمشاهده پروفایل

پژوهشگر

• Semantic Web
• Knowledge Graphs
• Linked Data
• +۵ مورد دیگر

Wouter Beek is a post-doctoral researcher at VU University Amsterdam and co-founder of Triply . His work focuses on Semantic Web technologies and knowledge-intensive applications, particularly through large-scale knowledge bases. He has co-developed key tools like the LOD Laundromat , LOD Search , and sameAs.cc . Email: w.g.j.beek@vu.nl Email: wouter@triply.cc Research Interests : Beek specializes in Semantic Web standards, data quality, and empirical semantics. His work bridges Web semantics with pragmatics, emphasizing innovative reuse of linked data across domains like geospatial analysis and historic data. He explores formalization of meaning within knowledge graphs to enable automated interpretation. Key Projects : LOD Laundromat : Infrastructure for crawling and cleaning linked data. sameAs.cc : Service addressing entity resolution via owl:sameAs. 3D SPARQL Visualization : Enhances geo-spatial and statistical interpretation of SPARQL results. Scientific Awards : Best Resource Paper Award at ESWC 2018 for 'Near Sameness is Somewhat the Same As SameAs'. Applications : His work impacts policy-making (e.g., energy savings investment strategies), real-estate analysis, and citizen services through knowledge graph integration.

Hannes Mühleisenمشاهده پروفایل

استاد

• Database Systems
• Data Engineering
• Embedded Analytics
• +۳ مورد دیگر

Hannes Mühleisen is Professor of Data Engineering at Radboud University Nijmegen and a Senior Researcher at Centrum Wiskunde & Informatica (CWI) in Amsterdam. He co-founded DuckDB Labs and created the DuckDB database management system. His research focuses on database systems and data engineering , with specific interests in embedded analytics , columnar processing , and query optimization . The DuckDB project has led to innovations in in-process analytical databases and extensible database architectures . Recent publications emphasize parser extensibility , external memory algorithms , and web-based data processing . His work bridges database engineering with data science through techniques like progressive indexing and tensor-accelerated queries . He maintains professional affiliations with: Radboud University Nijmegen (Academic) CWI Amsterdam (Research) DuckDB Labs (Industry) Contact information: Email: hannes@duckdblabs.com Professional profiles: Website , GitHub , LinkedIn

• International Relations
• Conflict Early Warning Systems
• International Organizations
• +۳ مورد دیگر

Alina Isakova is a Researcher and former Doctoral Researcher in the Research Training Group 'World Politics' at Bielefeld University (2020-2023). Since March 2024, she serves as a Research Associate with the project 'A Theory of World Entities' (ATOWE), funded by the German Research Foundation (DFG). Her research focuses on international organizations, conflict early warning systems, and cooperation structures among intergovernmental and non-governmental actors. She holds a Master's in International Economic and Political Studies from Charles University (Prague) and a Specialist degree in International Relations from Kyrgyz-Russian Slavic University. Education: 2010–2012: Master’s, Charles University, summa cum laude 2003–2008: Specialist (BA/MA), Kyrgyz-Russian Slavic University Research Interests: Alina explores how international organizations like the UN, EU, and OSCE construct and respond to global challenges such as violent conflicts. Her work employs discourse analysis to study cooperation norms, hierarchies, and institutional behaviors. Key areas include early warning mechanisms, securitization practices, and the role of international bureaucracies. Conference Contributions: She has presented extensively at venues like ECPR, ISA, and EWIS conferences, addressing themes like EU roles in conflict response, OSCE early warning models, and gender dynamics in institutional change. She co-organized workshops on gender equality strategies and global governance debates. Teaching: Since 2022, she has been a Teaching Assistant for qualitative data analysis courses at ECPR Winter and Summer Methods Schools. Labs/Teams: Core member of the RTG World Politics (Bielefeld University) and collaborates with institutions like the African Union Commission and the OSCE Documentation Centre.

Mayank Kejriwalمشاهده پروفایل

عضو هیئت علمی

• Knowledge Graphs
• Artificial Intelligence
• Neuro-symbolic AI
• +۷ مورد دیگر

Mayank Kejriwal is a Research Assistant Professor in the Department of Industrial and Systems Engineering at the University of Southern California (USC) and a Research Lead at the USC Information Sciences Institute (ISI). His work focuses on applying AI technologies for social good, particularly through knowledge graphs and neuro-symbolic AI. Education: PhD in Computer Science, University of Texas at Austin Research Interests: Dr. Kejriwal's primary research is in knowledge graphs (KG), neuro-symbolic AI, and complex systems. He explores how AI can address real-world issues such as human trafficking, crisis response, and healthcare. His work bridges theory and application, combining symbolic reasoning with modern machine learning techniques. He is also active in computational social science, network science, and AI ethics, with a strong emphasis on human-centered computing. Scientific Awards: USC Graduate Student Mentorship Award (2021) AAAS Early Career Award for Public Engagement with Science Finalist (2021) Yahoo! Faculty Research Engagement Program Recipient (2019) Copper Black Award for Creative Achievement, Mensa Foundation (2019) Key Scientific Challenge Award, Allen Institute for AI (2018) International Best Dissertation Award, Semantic Web Science Association (2017) Grants & Funding: His research has been funded by DARPA, corporate sponsors, and philanthropic organizations. He has led multiple projects under the MEMEX and other federal programs aimed at AI for social impact. Teaching & Mentorship: He teaches courses such as ISE 540: Text Analytics and ISE 599: Applied Predictive Analytics. He has received the USC Graduate Student Mentorship Award for his dedication to student development.

• Semantic Web
• RDF Data Management
• Knowledge Graphs
• +۵ مورد دیگر

Olivier Curé is a faculty member affiliated with Université Paris Est in France, specializing in semantic web technologies and knowledge engineering. His research focuses on distributed RDF processing, knowledge graph management, and edge computing adaptations of semantic technologies. Research Focus: Dr. Curé leads significant work in RDF stream processing systems (Strider engine), knowledge graph compression (LiteMat encoding), and privacy-preserving semantic data management. His recent work explores edge computing adaptations of knowledge graphs, real-time stream reasoning, and distributed SPARQL query processing. Key innovations include privacy frameworks for RDF anonymization and resource-efficient knowledge representation for IoT environments. Publication Trends: His 15 most recent publications (2020-2025) demonstrate a strong focus on: 1) Scalable RDF processing architectures, 2) Knowledge graph optimization for edge devices, 3) Privacy-enhancing techniques for semantic data, and 4) Distributed reasoning systems. This reflects an evolution from foundational RDF storage research toward adaptive, privacy-aware semantic systems for decentralized computing. Research Infrastructure: Dr. Curé contributes to multiple open-source projects including Strider (distributed RDF processing) and ZodiacEdge (Datalog engine), indicating leadership in semantic technology tooling development.