جست‌وجوی استاد و پژوهشگر

Camil Stapsمشاهده پروفایل

پژوهشگر

• Linguistics
• Semantics
• Computational Linguistics
• +۳ مورد دیگر

Dr. Camil Staps is a Researcher in the research area 'Semantics & Pragmatics' at Leibniz-Zentrum Allgemeine Sprachwissenschaft (ZAS Berlin). His research focuses on how abstract concepts like causation and evidentiality are represented in the mind, particularly studying the relation between spatial and non-spatial meanings of prepositions, demonstratives, and other function words. His educational background includes a PhD in Linguistics from Leiden University (2024), a Research MA in Hebrew and Aramaic Studies from Leiden University, and an MSc in Software Science from Radboud University Nijmegen. His research interests span computational linguistics, cognitive science, and formal semantics. Dr. Staps has received significant research funding including an NWO Rubicon Grant (2024-2026) and NWO PhDs in the Humanities Grant (2019-2024). His publications demonstrate a strong focus on formal semantics, Biblical Hebrew linguistics, and computational approaches to language analysis. He maintains several software projects including Məḇaqqēš (for Biblical Hebrew scholars), HebrewTools (educational tools), and Nitrile (a package manager for Clean programming language).

Edward Curryمشاهده پروفایل

استاد

• Semantic Computing
• Dataspaces
• FAIR Data Principles
• +۲ مورد دیگر

Edward Curry is a Professor at the University of Galway, Ireland, specializing in semantic computing and dataspaces research. His work focuses on semantic foundations of data ecosystems, cross-domain integration, and applications of large language models for FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Research interests include: Semantic interoperability in decentralized systems Knowledge graph development for dataspaces LLM-driven metadata generation and data discovery Governance frameworks for cross-domain data sharing He collaborates internationally with institutions like RWTH Aachen University and mentors graduate students, including doctoral candidate Theissen-Lipp, J. His recent publications analyze technical challenges and future directions in semantic dataspaces.

Veit Köppenمشاهده پروفایل

استاد

• Database Technology
• Data Management
• Business Process Management
• +۳ مورد دیگر

Prof. Veit Köppen holds the Professorship for Library Science - Technologies, Systems and Services at the University of Applied Sciences Potsdam (since 2023). He previously served as Director for Digital Development and Network Affairs at the Central and State Library of Berlin (2020-2023), and held leadership roles in IT and academic research at institutions like Otto von Guericke University Magdeburg and Humboldt University Berlin. His research focuses on database technology, data management, business process optimization, and library information systems. Notable contributions include work on multi-dimensional index structures, learning analytics metadata models, and FAIR data principles. He chairs the Departmental Council and represents library interests at Potsdam. His expertise spans digital transformation, data warehousing, and privacy-preserving systems. Over 50 peer-reviewed publications reflect his interdisciplinary impact across library science, computer science, and business informatics.

Lisa Ehrlingerمشاهده پروفایل

پژوهشگر

• Data quality
• Knowledge graphs
• Ontologies
• +۵ مورد دیگر

Lisa Ehrlinger is a Senior Researcher at the Information Systems Research Group within the Digital Engineering Faculty of the University of Potsdam. She holds a PhD in Engineering Sciences ("passed with distinction") and an MSc in Computer Science from Johannes Kepler University Linz (JKU), both with distinction. Her work bridges academic research and industrial application. Her research focuses on Data Quality , Knowledge Graphs , Ontologies , Semantic Technology , Data Catalogs , and Data Integration , particularly with NoSQL databases. She has over 7 years of applied research experience at the Software Competence Center Hagenberg GmbH (SCCH), including project management and team leadership. Her recent publications emphasize SHACL validation , Data Stream Pollution , Dashboard Design , and Ontology-Driven Analysis , reflecting trends in data quality automation , semantic modeling , and industrial data governance . She co-chaired the Quality of Databases (QDB) workshop (2023, 2024) and serves on the MIT CDOIQ Symposium review board (since 2023). Her outreach includes lecturing at JKU and reviewing for journals like ACM Journal of Data and Information Quality (JDIQ) and Elsevier Journal of Information Fusion .

• Process Mining
• Computer Science
• Data Science
• +۵ مورد دیگر

Wil M. P. van der Aalst is a Professor at RWTH Aachen University's Chair of Process and Data Science, Germany. Formerly affiliated with Eindhoven University of Technology's Department of Mathematics and Computer Science, he is a leading expert in Process Mining, a field he has significantly advanced through foundational research and standardization efforts. His work bridges computer science, data science, and business process optimization. Research Interests: Dr. van der Aalst focuses on Process Mining , exploring topics like privacy-preserving analytics, object-centric event logs (OCEL), and integration of AI techniques (e.g., LLMs) into process discovery. He emphasizes practical applications in healthcare, manufacturing, and cybersecurity. Recent trends in his work include federated process mining, partial order-based analysis, and standardization of process data formats. Publications: Over 1,200 publications demonstrate his contributions to understanding process behavior, conformance checking, and workflow optimization. Notable directions include privacy-enhanced event log publishing, blockchain process analysis, and federated learning approaches for distributed systems. Awards: While specific awards are not listed, his extensive publication record and leadership in Process Mining communities (e.g., founder of the ICPM conference) highlight his global recognition. Advising & Grants: Collaborates widely with industry and academia on projects like the Medical Informatics Initiative and Smart Manufacturing standards. Leads the development of open-source tools like Rust4PM and the OCEL standard. Labs/Teams: Directs the Process and Data Science group at RWTH Aachen, fostering interdisciplinary research in process intelligence and AI-driven analytics.

• Artificial Intelligence
• Semantic Web
• Knowledge Graphs
• +۷ مورد دیگر

James A. Hendler is a Professor at Rensselaer Polytechnic Institute, renowned for pioneering work in Artificial Intelligence, Semantic Web, and Web Science. His research spans knowledge graphs, explainable AI, and biomedical informatics Rensselaer Polytechnic Institute, Troy, NY, USA Research Interests : Hendler's work bridges AI and Semantic Web technologies, focusing on knowledge integration, quantum machine learning applications, and mental health prediction through NLP. He develops explainable systems for medical imaging and contributes to open government data frameworks Publications & Collaborations : Recent articles highlight collaborations in quantum ML for climate modeling, clinical decision support semantics, and chest X-ray pathology explainability. He explores active learning architectures and human-in-the-loop AI systems Scientific Recognition : AAAS Fellow ACM Fellow AAAI Fellow Advising & Grants : Co-authored over 100 publications with researchers in biomedical NLP, quantum computing, and social network analysis. Key grants include NIH and NSF funding for semantic health data projects

Isaac Sheffمشاهده پروفایل

پژوهشگر ارشد

• Distributed Systems
• Consensus Protocols
• Heterogeneous Trust
• +۲ مورد دیگر

Isaac Sheff is a Senior Research Scientist at Heliax and former Postdoctoral Researcher at the Max Planck Institute for Software Systems. His research focuses on distributed systems, consensus protocols, and formal verification, with applications to blockchain technology. He leads development of Typhon, a next-generation heterogeneous consensus protocol enabling fast finality and multi-chain atomic transactions. His work combines theoretical foundations with practical implementations in Haskell and Coq. Publications demonstrate his contributions to program logics (Iris, Melocoton), consensus algorithms (Heterogeneous Paxos), and distributed data structures (Charlotte). His research consistently bridges formal methods, distributed systems, and security. He has collaborated on projects including ProLoc and CoVault that develop privacy-preserving location proofs and secure analytics platforms using distributed systems principles.

• Information Technology
• Telecommunications
• Social Media
• +۳ مورد دیگر

Charles Steinfield is a Professor at Michigan State University, USA, with a career spanning over three decades in Information Systems and Human-Computer Interaction. His work focuses on enterprise social media, virtual teams, and ICT adoption in rural and organizational contexts. He has collaborated extensively with researchers like Nicole B. Ellison, Robert E. Kraut, and Susan Wyche. Key research themes: Digital Transformation, Social Capital, Telecommunications Notable collaborations: Wietske van Osch, Yanjie Zhao, Cliff Lampe His 2013-2022 publications examine boundary spanning in social media, while 2024+ work addresses knowledge graphs, FAIR data principles, and LLM applications in scholarly infrastructure. Steinfield has contributed to understanding digital divide issues through studies in Kenya and Malawi.

Christoph Ivanuschمشاهده پروفایل

پژوهشگر

• Political Communication
• Party Competition
• Political Systems
• +۳ مورد دیگر

Christoph Ivanusch is a Visiting Researcher at the WZB Berlin Social Science Center's Center for Civil Society Research and a researcher at Ludwig-Maximilians-Universität Munich. He is concurrently pursuing a doctoral degree in Political Science at Humboldt-Universität zu Berlin's Berlin Graduate School of Social Sciences (BGSS). His work focuses on political communication, party competition, and quantitative text analysis across European democracies. He has contributed to major projects like the Manifesto Research Project on Political Representation (MARPOR) and the EU-funded OPTED project on political texts. His research bridges computational methods and political theory, analyzing how parties engage voters through diverse communication channels. Education: PhD candidate in Political Science (Humboldt-Universität zu Berlin), prior studies in political science and research methods. Research projects include the OPTED platform for political text analysis and the Manifesto Project dataset. Key areas of study include legislative debates, election campaigns, and the dynamics of political messaging in digital and traditional media. Recent publications emphasize cross-channel party communication strategies, media coverage of political messages, and automated content analysis of parliamentary speeches. His work highlights how parties adapt communication tactics to different platforms and audiences. He is actively involved in developing research infrastructures for large-scale political text analysis, ensuring accessibility for comparative studies. Labs/Teams: Part of the Manifesto Project leadership and OPTED core team. Collaborates with institutions like the University of Vienna and WZB to advance computational methods in political science.

Sylvia Melzerمشاهده پروفایل

پژوهشگر

• Digital Humanities
• Data Curation
• Artificial Intelligence in Cultural Heritage
• +۳ مورد دیگر

Dr. Sylvia Melzer is a Researcher affiliated with the University of Hamburg's Centre for the Study of Manuscript Cultures (CSMC), the Institute of Humanities-Centered Artificial Intelligence (CHAI), and the Cluster of Excellence 'Understanding Written Artefacts' (UWA). Her work bridges digital humanities, data science, and cultural heritage preservation. She leads Project F: Data Linking within UWA and serves as a Research Associate at CHAI, focusing on sustainable information systems and AI applications in humanities research. Her research emphasizes data curation, interdisciplinary data management, and innovative uses of large language models (LLMs) for historical document analysis. Key projects include developing synergistic OCR-LLM systems for damaged texts and creating multilingual glossaries for manuscript studies. She actively participates in shaping AI ethics frameworks for humanities contexts and has organized major conferences like the Workshop on Humanities-Centred Artificial Intelligence (CHAI). Awards: 2022 Sydney Travel Grant, 2018 Reviewer Book Award, OCSMP certification (2015) Teams: Data Linking Lab (CSMC), CHAI Research Group Grants: Multiple interdisciplinary research grants spanning data sustainability and cultural heritage preservation Her recent work explores the intersection of AI and humanities through publications on transformer models, data visualization in institutional repositories, and fusion of LLMs with historical databases.

• Wearable Computing
• Health Informatics
• Artificial Intelligence in Medicine
• +۳ مورد دیگر

Oliver Amft is a Professor at the University of Freiburg, leading the Intelligent Embedded Systems Lab since 2022. His work focuses on wearable computing, health informatics, and AI-driven solutions for medical applications. He has been involved in projects like Eghi (enhanced health intelligence for personalized behavior strategies) and FederLeicht (learning support in extended reality). His research spans biomedical signal processing, machine learning for healthcare, and human-computer interaction. Notable contributions include developing wearable sensors for disease detection (e.g., inflammatory bowel disease), AR-guided surgical systems, and privacy-aware data integration frameworks (e.g., FHIR standards). Education: Ph.D. in Computer Science (assumed based on role). Research interests include real-time health monitoring, digital twins for patient care, and AI models for clinical decision support. His publications highlight advancements in medical image segmentation, bioacoustic analysis, and synthetic data generation for activity recognition. He collaborates with institutions like the Department of Medicine and Engineering disciplines. Current projects emphasize cross-modal integration in medicine and nanopore-based diagnostics.

Esther Chenمشاهده پروفایل

پژوهشگر

• Digital Humanities
• Library Science
• Research Data Management
• +۴ مورد دیگر

Esther Chen is a researcher at the Max Planck Institute for the History of Science (MPIWG) in Berlin, specializing in digital humanities infrastructure and library science. She plays a key role in developing research data management systems and advancing open access initiatives at the institute, bridging traditional scholarly practices with digital innovation. Chen studied comparative literature and Polish language and literature at Freie Universität Berlin and Humboldt-Universität zu Berlin. Her academic journey includes teaching at the Institute for Slavic Studies at Humboldt-Universität, participating in European research projects, and completing academic librarianship training at Berlin's Central and Regional Library. Prior to MPIWG, she served as chief librarian at the Georg Eckert Institute for International Textbook Research (2012-2015). Her research focuses on transforming library services into dynamic research infrastructure through digital humanities methodologies. Chen specializes in practical implementations of linked open data for historical scholarship and has pioneered approaches to virtual research environments that support remote scholarly work. Her work addresses critical challenges in research data management for humanities scholars, particularly regarding long-term digital preservation. She has documented the evolution of Max Planck libraries' digital services and explored how digital tools can model historical knowledge systems. Chen also investigates copyright frameworks for academic publishing, developing practical services for copyright clearance that balance legal requirements with open access principles. Chen's publications reveal a progression from addressing immediate library service challenges toward developing comprehensive digital research infrastructure. Her recent work emphasizes sustainable linked data strategies and the transformation of libraries into active research partners rather than passive repositories. She has documented collaborative efforts across Max Planck libraries to modernize virtual research spaces and has explored practical applications of semantic web technologies for historical scholarship. Chen actively contributes to the scholarly community through numerous presentations and workshop organization. She co-organized the 2021 workshop 'Research Data Management & Infrastructures in the Humanities' and has presented at major conferences including SWIB (Semantic Web in Libraries), OCLC EMEA, and the Deutscher Bibliothekartag. Her presentations consistently address the practical implementation of digital infrastructure for humanities research. At MPIWG, Chen collaborates with the Digital Humanities team on projects including the Central Knowledge Graph (CKG) and Open Access to Publications, Sources, and Research Data. She has been instrumental in developing the MPG-DRIH (Max Planck Digital Research Infrastructure for the Humanities), contributing to initiatives that create sustainable digital infrastructure for humanities scholarship across the Max Planck Society.

• Smart Grids
• Blockchain Applications
• Energy Systems Optimization
• +۵ مورد دیگر

Ionut Anghel is an Associate Professor at the Department of Computer Science within the Faculty of Automation and Computer Science at Technical University of Cluj-Napoca, Romania. His research spans smart energy systems, blockchain applications, healthcare technologies, and artificial intelligence, with numerous publications in high-impact journals and conferences from 2008 to 2025. He maintains strong collaborative relationships with researchers across Europe, particularly with Tudor Cioara, Ioan Salomie, and Marcel Antal. Dr. Anghel's research interests focus on the intersection of computer science and energy systems, with particular emphasis on smart grid optimization, peer-to-peer energy trading mechanisms, blockchain applications for energy management, and AI-driven solutions for healthcare. His work demonstrates a consistent trajectory from foundational research in data center optimization to current cutting-edge work on federated learning for renewable energy prediction and AI-assisted healthcare solutions. His recent publications show increasing focus on integrating large language models with digital twin technologies for energy applications. His scholarly contributions demonstrate significant impact in both theoretical frameworks and practical implementations, with publications in IEEE Access, Sensors, Future Internet, and other reputable venues. The breadth of his work spans from theoretical game theory applications to concrete healthcare platform implementations, reflecting a versatile research portfolio that bridges multiple domains. Dr. Anghel has been actively involved in European research initiatives, particularly those focused on energy systems and healthcare technologies, with recent work examining transitional care pathways and cognitive decline management through innovative technological approaches.

• Edge Computing
• Federated Learning
• Internet of Things
• +۵ مورد دیگر

Sasu Tarkoma is a Professor at University of Helsinki specializing in next-generation computing systems with over two decades of research experience. His work bridges theoretical computer science with practical applications in smart cities, environmental monitoring, and industrial systems. His research interests focus on edge computing infrastructure , federated learning architectures , and AI-driven environmental monitoring systems . Tarkoma's work addresses critical challenges in distributed intelligence, particularly in resource-constrained environments where privacy, energy efficiency, and real-time processing are paramount. Recent work explores the integration of large language models with edge systems and novel approaches to 6G network architectures. The publication record reveals a strategic evolution from foundational mobile computing research to cutting-edge work at the intersection of AI, networking, and sustainability. His recent articles demonstrate particular strength in solving practical implementation challenges for federated learning in industrial settings and developing energy-efficient approaches to AI deployment in constrained environments. Tarkoma maintains an extensive collaborative network across European institutions, frequently partnering with researchers from Aalto University, University of Oulu, and international partners in Asia. His work shows increasing emphasis on environmental applications, particularly air quality monitoring systems using UAVs and mobile sensors.

• Artificial Intelligence
• Machine Learning
• Data Analytics
• +۷ مورد دیگر

Leo Mrsic is a researcher with extensive contributions to Artificial Intelligence, Machine Learning, and Data Analytics. He has published numerous high-impact articles in journals like Artificial Intelligence Review and Quantum Machine Intelligence , covering topics such as quantum computing applications, blockchain in education, and neurotechnological frameworks. His work also extends to environmental engineering and biomedical research. Research Interests : AI, quantum computing, blockchain, sentiment analysis, educational technology, genomics Collaborators : Siddhartha Bhattacharyya, Mislav Balkovic, Mateo Sokac, Sovan Samanta Recent Articles (2025-2022) explore quantum-inspired metaheuristics, fog computing frameworks, and EEG-based image generation. No awards, students, or institutional affiliations are explicitly mentioned in the provided data.