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Stefan WoltranView profile

Professor

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Abstract Argumentation
• +3 more

Stefan Woltran is a Professor at TU Wien, affiliated with the Research Group Databases and Artificial Intelligence. His work focuses on formal methods in AI, particularly in abstract argumentation frameworks, knowledge representation, and computational logic. He leads research initiatives exploring semantics analysis, preference handling in argumentation, and algorithmic optimizations for complex reasoning tasks. His contributions bridge theoretical foundations with practical applications in logic programming and automated reasoning. Research Interests: Abstract Argumentation (semantics, expressiveness, complexity) Answer Set Programming (grounding optimization, formal properties) Knowledge Representation (formal systems, computational complexity) Algorithm Design (tree decompositions, dynamic programming) Publications reflect advancements in argumentation theory, logic-based AI, and algorithmic problem-solving. He supervises PhD students in these areas and collaborates on projects addressing bottlenecks in automated reasoning systems.

• Cyber-Physical Systems
• Formal Verification
• Programmable Logic Controllers
• +3 more

Ignacio David Lopez Miguel is a PreDoc Researcher at the Cyber-Physical Systems department of Vienna University of Technology (TU Wien). His research focuses on formal verification techniques for safety-critical systems, particularly in the context of Programmable Logic Controllers (PLCs) used in industrial and high-stakes environments like CERN's Large Hadron Collider (LHC) cooling systems. Current projects include TAIGER (2023–2027), addressing neural network verification for PLC code. Collaborates with institutions such as CERN, GSI, and NASA on safety-critical control systems. Research Themes : Integration of formal verification with AI/ML components Runtime enforcement in cyber-physical systems Ethical considerations in engineering design Automated translation of natural language requirements to formal specifications His work spans interdisciplinary domains, connecting computer science, control theory, and engineering ethics through rigorous verification methodologies.

• Answer Set Programming
• Logic Programming
• Knowledge Representation
• +2 more

Wolfgang Faber is a researcher at Vienna University of Technology (TU Wien) specializing in Knowledge-Based Systems within the Faculty of Informatics. Holding the position of Privatdozent, he has completed his habilitation and is qualified to teach at the university level. His academic work centers on Answer Set Programming (ASP), Logic Programming, and Knowledge Representation, with significant contributions to theoretical foundations in these fields. Dr. Faber's research spans multiple areas of computational logic: Answer Set Programming and its theoretical underpinnings Epistemic logic programs and equivalence properties Knowledge representation and reasoning systems Nonmonotonic reasoning formalisms Integration of logic programming with external data sources His publication history reveals a sustained focus on theoretical aspects of ASP, with particular emphasis on program equivalence concepts (strong equivalence, uniform equivalence), computational complexity analysis, and applications to knowledge representation. Over two decades, his research has evolved from foundational work in disjunctive logic programming to specialized topics in epistemic reasoning within ASP frameworks. Dr. Faber has led and participated in numerous research projects including START (2014-2022) on Uniform Equivalence of Epistemic Logic Programs, SemDat (2012-2016), and multiple projects related to hybrid knowledge bases and Answer Set Programming from 2005-2015. His collaborative research extends across European institutions, evident through extensive co-authorship with researchers like Thomas Eiter and Stefan Woltran. While specific awards aren't documented in the available information, his sustained research output and leadership in multiple projects indicate significant recognition within his field. Dr. Faber has made substantial contributions to major systems in the field, most notably the DLV system for knowledge representation and reasoning, which has influenced both academic research and practical applications of Answer Set Programming.

• Knowledge Representation
• Artificial Intelligence
• Temporal Logic
• +2 more

Davide Solda is a Researcher in the Knowledge-Based Systems group at Vienna University of Technology. His work focuses on formal methods in artificial intelligence, particularly temporal logic and knowledge representation. Research interests include: computational logic, multi-agent systems, epistemic planning, and automated reasoning techniques. His investigations bridge theoretical foundations with practical applications in system verification. Recent publications demonstrate consistent focus on temporal extensions of logical frameworks, with progressive applications in multi-agent scenarios and runtime verification contexts.

• Artificial Intelligence
• Cybersecurity
• Optimization Algorithms
• +3 more

Alice Tarzariol is a Researcher at the Institut für Artificial Intelligence und Cybersecurity within the Faculty of Technical Sciences at Alpen-Adria-Universität Klagenfurt. She specializes in computational logic, optimization algorithms, and their applications in artificial intelligence. Her research focuses on advancing Answer Set Programming (ASP) techniques for complex problem-solving, including production scheduling, symmetry breaking, and constraint learning. She also explores interdisciplinary applications such as cancer data analysis through logic programming frameworks. Her work emphasizes improving algorithmic efficiency and developing tools for combinatorial optimization, formal verification, and bioinformatics. She contributes to projects like the institute’s efforts to strengthen regional knowledge transfer and serves on the Curricularkommission für das Erweiterungscurriculum Gender Studies. Her research spans both theoretical advancements in computational logic and practical implementations in industrial and medical domains. Key themes in her publications include symmetry detection and lifting, constraint satisfaction, and inductive logic programming. Recent work highlights declarative approaches to production scheduling and efficient symmetry-breaking methods. Her research has implications for automated decision-making, systems modeling, and data-driven healthcare solutions.

• Artificial Intelligence
• Cybersecurity
• Computer Science
• +3 more

Michael Morak is a Professor at the Department of Artificial Intelligence and Cybersecurity, Alpen-Adria-Universität Klagenfurt, affiliated with the Faculty of Technical Sciences. He holds the titles Privatdozent, Diplom-Ingenieur, and Doctor. His research focuses on artificial intelligence, cybersecurity, and computer science, with notable contributions in logic programming, answer set programming, and algorithmic methods. He has led and contributed to multiple research projects funded by entities like the Austrian Research Promotion Agency (FFG) and the Austrian Agency for International Cooperation in Education (OeAD), addressing topics such as multi-agent systems, radar simulation, and educational technology. His work spans theoretical advancements, including reversibility in planning and dynamic programming, as well as practical applications like interactive SQL learning tools (aDBenture). He collaborates with industry partners, including Infineon Technologies, and has published extensively in top-tier conferences and journals. Morak’s teaching emphasizes innovative methods in computer science education, leveraging game-based learning and interactive platforms to enhance student engagement. Key areas of research include formal methods in AI, algorithmic complexity, and the integration of logic programming with real-world systems. His projects often bridge academia and industry, aiming to solve complex challenges in cybersecurity, robotics, and educational innovation.

• Artificial Intelligence
• Knowledge Engineering
• Machine Learning
• +3 more

Konstantin Schekotihin is an Associate Professor at the Institute of Artificial Intelligence and Cybersecurity , part of the Faculty of Technical Sciences at Alpen-Adria-Universität Klagenfurt. His research focuses on AI-driven solutions for semiconductor manufacturing, failure analysis, and multi-agent systems. He specializes in reinforcement learning, scheduling optimization, and neuro-symbolic AI applications. His work bridges theoretical advancements with industrial challenges such as semiconductor fab automation and real-time process monitoring. He has collaborated with organizations like the Austrian Research Promotion Agency (FFG) and Infineon Technologies. Key research areas include: AI for semiconductor failure analysis workflows Reinforcement learning in manufacturing scheduling Multi-agent systems in immersive VR environments Neuro-symbolic AI for defect routing Predictive modeling for equipment maintenance Recent projects involve optimizing ion implantation processes, developing FA ChatBots, and improving social presence in VR simulations. His work emphasizes scalability, explainability, and real-world applicability of AI systems.

Axel PolleresView profile

Professor

• Semantic Web
• Ontology Languages
• Web Databases
• +7 more

Axel Polleres is a full professor at the Vienna University of Economics and Business (WU Wien), leading the Department of Information Systems and Operations Management and heading the Data Management group within the Institute for Data, Process and Knowledge Management. He specializes in Semantic Web technologies, knowledge representation, and open data. His work includes contributions to SPARQL, RDF, and W3C standards. Education: PhD and Habilitation in Computer Science (TU Wien) MSc in Computer Science (TU Wien) Research Interests: Semantic Web, Ontology Languages, Linked Data Nonmonotonic Reasoning, Answer Set Programming Query Languages (SPARQL), Data Integration Open Data ecosystems and Quality Assessment Recent Articles Trends: Focusing on knowledge graph evolution, constraint validation (SHACL), and open data pipelines, with applications in city data and semantic web services. His work bridges theoretical foundations with practical implementations. Awards: IEEE 2015 Best Paper Award RR2010 Best Paper Award ISWC2009 In-use Track Best Paper Advising & Labs: Advisor to over 30 PhD/MSc students. Leads the Data Management group at WU, focusing on open data systems and semantic technologies. Involved in projects like FRESH, OMEGA, and W3C standardization efforts.

• Knowledge Representation
• Description Logics
• Computational Logic
• +3 more

Magdalena Ortiz is a Full Professor and Head of the Knowledge-Based Systems Research Unit at TU Wien, specializing in Knowledge Representation and Reasoning with a focus on Description Logics (DLs). Her work emphasizes integrating DLs with database systems, particularly in query languages and reasoning algorithms. She leads research in semantic technologies, ontology-mediated query answering, and formal methods for data validation (e.g., SHACL). Research interests include expressive query languages, computational complexity of DL reasoning, and applications in graph databases and cloud security. She has extensive experience in EU-funded projects (e.g., FRESH, KtoAPP) and serves editorial roles in AI conferences/journals. Her teaching includes advanced courses on Description Logics, Logic, and Ontology Engineering. Notable contributions include advancements in SHACL validation, Datalog rewritings for ontology-mediated queries, and reasoning with closed predicates. She advises multiple PhD students and collaborates internationally on topics like temporal equilibrium logic and OBDA systems.

• Digital Innovation
• Business Process Management
• License Management
• +3 more

Giray Havur serves as a Researcher at the Institute for Innovation Systems within the Department of Digital Business and Innovation at St. Pölten University of Applied Sciences, focusing on digital transformation at the intersection of technology, law, and business processes. His research program centers on three critical domains: License Management Systems : Pioneering the DALICC framework for automated license clearance, customization, and compatibility checking in digital asset ecosystems Business Process Optimization : Applying Answer Set Programming to resource allocation, risk-aware process fragmentation, and decision-intensive workflow management Sustainable Data Governance : Developing Digital Product Passport architectures (DPP4ALL) for transparent supply chain tracking and circular economy applications Analysis of his 2021-2023 publications reveals a strategic shift toward operationalizing semantic technologies for regulatory compliance, with increasing emphasis on European sustainability initiatives and decentralized data exchange architectures. His work consistently bridges theoretical formal methods with practical industry applications. Dr. Havur actively contributes to major research projects including OpenDALICC (open license management framework), DPP4E (Digital Product Passport for Europe), and ECO-TCO (sustainable business modeling), collaborating with EU institutions and industry partners to advance digital innovation standards.

• Artificial Intelligence
• Computational Intelligence
• Database Systems
• +4 more

Univ.-Prof. Wolfgang Faber is a Professor at the Alpen-Adria-Universität Klagenfurt (AAU), affiliated with the Institute for Artificial Intelligence and Cybersecurity. He holds academic positions in both computer science and engineering disciplines. His research focuses on artificial intelligence, computational intelligence, and theoretical computer science, with particular expertise in answer set programming (ASP), knowledge representation, and formal methods. His work integrates areas like ontology reasoning, action reversibility, and hybrid knowledge bases. Education details are not explicitly stated in the provided text, but his professional trajectory reflects advanced qualifications in engineering and computer science. Research priorities include database systems, semantic technologies, and formal languages, often addressing challenges in meta-reasoning and computational logic. His contributions span theoretical advancements and practical applications, such as ASP-based tools for planning and reasoning systems. Notable research trends include the development of efficient ASP solvers, evaluation of Datalog tools for OWL 2 QL meta-reasoning, and exploration of epistemic logic programs. His work on action reversibility in STRIPS planning and paracoherent answer set computation highlights his focus on bridging formal logic with real-world problem-solving. Collaborations and projects involve international conferences and workshops, including contributions to ICLP, JELIA, and Reasoning Web venues. Wolfgang Faber's professional engagement extends to academic service roles, including membership in the AAU Senate. His research is supported through grants and collaborations, though specific grant details are not provided here. He maintains an active presence in academic communities via ORCID and Google Scholar profiles, with a prolific publication record in top-tier conferences and journals.

• Databases
• Database Theory
• Complexity Theory
• +2 more

Christoph Koch is an Associate Professor at Technische Universität Wien specializing in databases and artificial intelligence. His research spans database theory, complexity theory, and logic in computer science, with a focus on XML processing, query optimization, and parallel data science techniques. Lead projects: KnowledgeGraph (2020–2028), HINT (2012–2017), Weblearn (2005–2008) Developed the Lixto visual extraction system and contributed to DLV knowledge representation framework Supervised T. Lukasser's diploma thesis on XPath query processing

• Knowledge Representation
• Description Logics
• Ontology Engineering
• +4 more

Sanja Lukumbuzya is a PostDoc Researcher at the Knowledge-Based Systems group (E192-03) of Vienna University of Technology. Her work bridges formal logic and practical data systems, focusing on ontology-mediated data management, description logics, and business process challenges. Research Interests Ontology-Based Data Access (OBDA) Description Logics and Datalog Rewriting Process Mining and Workflow Analysis Hybrid Reasoning Systems Incomplete Data Handling Computational Complexity in Knowledge Bases Affiliations Vienna University of Technology, Austria Researcher in projects KtoAPP (2018–2025) and OMEGA (2017–2022) Publications Trends Her recent work addresses algorithmic complexity in expressive logics (2024), coNP expressiveness in ontology queries (2023), and practical BPM challenges (2023). Earlier studies focused on bounded predicates (2021), hybrid ASP-ontology frameworks (2020), and dishonesty modeling (2018).

• Answer-Set Programming (ASP)
• Explainable AI
• Logic in Artificial Intelligence
• +3 more

Tobias Geibinger is a PreDoc Researcher at the Institute of Logic and Computation of Vienna University of Technology , supported by a DOC Fellowship from the Austrian Academy of Sciences. His work focuses on explainability in Answer-Set Programming (ASP), particularly for advanced language features and hybrid ASP systems. Education: BSc, Dipl.-Ing. (Master's equivalent) in Computer Science Projects: CD Laboratory for AI and Optimization (2017–2025), KIRAS-PrEMI (2019–2022), ARTIS (2017–2025) His research combines logic programming with constraint programming and hybrid methods to solve industrial scheduling problems. This includes automated test laboratory scheduling, photolithography job scheduling, and pandemic-era physician scheduling. Recent work investigates neurosymbolic integration and contrastive explanation frameworks. Selected publications analyze ASP optimization techniques for parallel machine scheduling, large-neighborhood search strategies, and nonmonotonic paraconsistent logics. These contributions align with broader trends in declarative AI and logic-based optimization. Scientific Recognition: ASAI Master Thesis Prize (2023)

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Logic Programming
• +5 more

Thomas Eiter is a Full Professor at the Vienna University of Technology (TU Wien) in the Department of Knowledge-Based Systems, Faculty of Informatics. His research focuses on artificial intelligence, knowledge representation and reasoning, logic programming, computational logic, and neurosymbolic AI integration. He leads projects in declarative problem-solving, intelligent agent systems, and stream reasoning frameworks like LARS. Eiter has contributed to foundational work in answer set programming (ASP), algebraic reasoning, and their applications in scheduling, robotics, and real-time data processing. He has extensive international collaborations, including EU-funded projects like HumanE-AI-Net and the Austrian Science Fund (FWF) initiatives. His work emphasizes bridging symbolic AI with modern machine learning techniques, particularly in visual question answering and neural-symbolic systems. Eiter has supervised numerous PhD students and maintains active roles in academic leadership, including editorial boards of journals like Theory and Practice of Logic Programming . Key contributions include development of the DLVHEX system for hybrid knowledge representation, optimization frameworks for ASP, and methodologies for stream reasoning in dynamic environments. His research also addresses ethical AI through projects like the TAIGER initiative, focusing on training AI agents with ethical rules.