جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Optimization
• Scheduling
• +۴ مورد دیگر

Marie-Louise Lackner is a Research Fellow (PostDoc Researcher) in the Department of Databases and Artificial Intelligence at Technische Universität Wien. She holds Diplom-Ingenieur and Dr. techn. degrees and actively contributes to the CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling (2017–2025). Her research focuses on Artificial Intelligence and Optimization , with emphasis on industrial scheduling, constraint programming, and algorithm design. Key domains include: Industrial oven scheduling and production leveling Metaheuristics (simulated annealing, large neighborhood search) Multi-objective optimization in manufacturing systems Combinatorial mathematics and discrete structures Her publications demonstrate a strong trajectory in applied optimization , with recent work concentrating on energy-efficient scheduling algorithms for electronic manufacturing, while earlier research explored permutation patterns and social choice theory. Methodologies consistently integrate theoretical computer science with industrial problem-solving. She supervises graduate researchers, including P. Malik's work on memetic algorithms for production leveling. Grant involvement includes the CD Laboratory project focused on AI-driven planning systems. Lackner is affiliated with the CD Laboratory for Artificial Intelligence and Optimization, conducting applied research in industrial scheduling systems within TU Wien's Databases and AI group.

• Data Management
• Reproducibility in Science
• Semantic Web Technologies
• +۳ مورد دیگر

Dr. Tomasz Miksa is a Senior Scientist at TU Wien's Department of Data Science, specializing in machine-actionable data management plans (maDMPs), reproducibility frameworks, and data stewardship. His work bridges semantic web technologies, automated workflows, and interdisciplinary data governance. He leads projects like OS Trails (2024–2027) and FAIR-AI , focusing on synchronizing research data services and ensuring FAIR (Findable, Accessible, Interoperable, Reusable) principles. Miksa holds a PhD in Computer Science from TU Wien (2016) and has supervised numerous theses on topics like reproducible query processing and DMP integration. He actively contributes to initiatives such as FAIR Data Austria and openEO API standardization, emphasizing sustainable data practices across disciplines. Research interests include semantic representation of DMPs, automated validation tools, and frameworks for auditable privacy-preserving data analysis. His work on data citation mechanisms and evolving database schemas ensures long-term reproducibility in fields like environmental science and earth observation. Miksa collaborates internationally, co-editing special collections on data management planning and publishing in journals like ACM Transactions on Management Information Systems and IEEE eScience . Key contributions include the DCSO ontology for DMPs, the WellFort platform for privacy-aware data analysis, and frameworks for identifying software dependencies in biomedical workflows. His teaching focuses on data stewardship, with courses like Data Stewardship VO/UE addressing national and institutional strategies. Ongoing efforts aim to integrate machine-actionable DMPs with institutional repositories and cloud-based research infrastructures.

Anouk Michelle Oudshoornمشاهده پروفایل

پژوهشگر

• Semantic Web Technologies
• Ontology Engineering
• Description Logics
• +۳ مورد دیگر

Anouk Michelle Oudshoorn is a PhD candidate and researcher at the Department of Knowledge-Based Systems, Institute of Logic and Computation, Technical University of Vienna. Her research focuses on integrating SHACL constraints with Description Logics and Ontology Engineering. She holds an MSc in Logic from the University of Amsterdam (ILLC) and dual BSc/BA degrees in Mathematics and Philosophy from Radboud University, Nijmegen. Education: PhD Candidate (2022–present), Technical University of Vienna MSc in Logic (2020–2022), University of Amsterdam BSc Mathematics & BA Philosophy (2017–2020), Radboud University Her research explores formal validation mechanisms for semantic technologies, emphasizing interoperability between SHACL and OWL ontologies. She has conducted research visits at Umeå University (2023) and TU Dresden (2024). Notable contributions include work on SHACL-Description Logic combinations and Vossian antonomasia generation for Wikidata. Awards: Netidee Stipend (2023) 2nd Prize Best Poster Award (ISWC 2023) Teaching: She has served as a teaching assistant for courses including 'Logic and Reasoning in Computer Science', 'Description Logics and Ontologies', and 'Knowledge-Based Systems' at TU Wien. Additional experience includes mathematics tutoring and logic instruction. Sustainability: Prioritizes train travel for international conferences to reduce environmental impact, undertaking extensive rail journeys across Europe.

• Logic Programming
• Computational Complexity
• Nonmonotonic Reasoning
• +۴ مورد دیگر

Mantas Simkus is an Assistant Professor at TU Wien's Institute of Logic and Computation, affiliated with the Database and Artificial Intelligence Group. He previously held an Associate Professor position at Umeå University (Sweden) within the Wallenberg AI, Autonomous Systems and Software Program (WASP). He leads the FWF-funded project 'KtoAPP: Compiling Knowledge into Applications' and contributes to the Cluster of Excellence 'Bilateral Artificial Intelligence'. His research focuses on logic-based data management, knowledge representation, and nonmonotonic reasoning, with applications in semantic web technologies and ontology engineering. Education: Bachelor's in Computer Science from Vilnius University. Research interests include logic programming, computational complexity, description logics, and their integration with databases. He explores techniques for efficient query answering, schema validation (e.g., SHACL), and reasoning under incomplete information. His work bridges theoretical foundations (e.g., complexity analysis, formal semantics) with practical systems (e.g., ontology-mediated query processing). Key projects include 'KtoAPP' (2018–2025), investigating automated knowledge compilation, and contributions to the 'SemDat' and 'OMEGA' initiatives. He teaches courses on deductive databases and semi-structured data at TU Wien. He actively participates in academic service: co-chair of RuleML+RR 2024, editorial board member of the Artificial Intelligence journal, and former co-chair of DL 2019. His research group collaborates on topics like graph databases, answer set programming, and hybrid knowledge representation systems.

• Graph Data Management
• RDF and Semantic Web
• Database Theory
• +۳ مورد دیگر

Maxime Jakubowski is a PostDoc Researcher at TU Wien's Faculty of Informatics, affiliated with the Databases and Artificial Intelligence research group. Based in Room HA0320 at Favoritenstrasse 9, he can be contacted at maxime.jakubowski@tuwien.ac.at and maintains an ORCID profile (0000-0002-7420-1337). His research centers on graph data management within the Semantic Web ecosystem, specializing in RDF validation through shape constraint languages like SHACL and ShEx. He investigates formal foundations, expressiveness boundaries, and practical implementations including SQL compilation and neighborhood-based graph description. Current projects include FRESH (2021–2026), KtoAPP (2018–2025), and TARGET (2024–2028), focusing on graph data theory and implementation. Recent publications (2021–2025) demonstrate consistent contributions to RDF validation standards, with 14 articles addressing shape language formalization, compilation techniques, and provenance tracking. His work bridges theoretical database concepts with industrial applications in knowledge graph validation. Dr. Jakubowski supervises bachelor theses and teaches courses including Management of Graph Data (192.161) and Project in Computer Science. His research collaborations span international projects and the Dagstuhl Seminar 24102 on Shapes in Graph Data. He is an active member of the Databases and Artificial Intelligence research group, contributing to TU Wien's leadership in graph data management and Semantic Web technologies through both theoretical research and practical tool development.

• Databases
• Programming Languages
• Query languages and data models
• +۱۱ مورد دیگر

Peter Buneman is currently a Professor of Database Systems at the University of Edinburgh , affiliated with the School of Informatics and the Foundations of Computer Science Laboratory . Previously, he held a Professor of Computer Science position at the University of Pennsylvania from 1975 to 2001, progressing from assistant to full professor. Education: PhD in Mathematics (1970), University of Warwick (Supervisor: E.C. Zeeman) MA in Mathematics (1966), University of Cambridge Research Interests: His work spans databases (semistructured data, XML, data provenance, distributed databases), programming languages (type systems, functional languages, semantics), and interdisciplinary areas like mathematical phylogeny , neural models , and applications of computers in the humanities . He has also contributed to database interfaces, knowledge bases, and data modeling. Scientific Awards: Member of the Order of the British Empire (2013) Fellow of the Royal Society (2009) Fellow of the Royal Society of Edinburgh (2004) Royal Society Wolfson Research Merit Award (2002) ACM Fellow (1999) Multiple Test of Time Awards (SIGMOD, ICDT) Broadband Awards from Nextgen Challenge and European Commission Additional Roles: Served as Graduate Chairman at University of Pennsylvania (1981-1987) and held visiting research positions at INRIA (France), Kyoto University (Japan), and Imperial College London.

• Cybersecurity
• Information Security
• Computer Science
• +۴ مورد دیگر

Gerald Quirchmayr is a Professor at the Faculty of Computer Science , leading the Research Group Multimedia Information Systems . His work focuses on Cybersecurity , Information Security , and Privacy Requirements Engineering , with applications in logistics, e-health, and cybersecurity education. Recent research trends include the integration of graph databases for ICT risk models, situational awareness in cybersecurity systems, and privacy-aware software development methodologies. Key sub-fields span Logistics Security Contextual Integrity Cybersecurity Education Data Flow Diagrams Knowledge Graphs Risk Management Scientific Awards Best Paper Award (2016) for 'Implementation of a Generic ICT Risk Model using Graph Databases' Quirchmayr actively contributes to educational initiatives , including the Sec Tech project (2016-2018) for cybersecurity teaching and the ongoing Dynamic Cybersecurity Management project (2022-2025). His lab develops tools like PrivacyStory to enhance privacy awareness in user stories.