Find Academic Supervisors

Sotirios BatsakisView profile

Research Fellow

• Knowledge Representation
• Semantic Web
• Spatio-Temporal Reasoning
• +4 more

Dr. Sotirios Batsakis is a Senior Research Fellow at the University of Huddersfield, School of Computing and Engineering. He holds a diploma in Computer Engineering and Informatics from the University of Patras (Greece) with highest distinction, and a Master’s/Ph.D. in Electronic & Computer Engineering from the Technical University of Crete. His work contributes to UN Sustainable Development Goals through research in knowledge representation, semantic web, and spatio-temporal reasoning. Centre for Planning, Autonomy and Representation of Knowledge Centre of Artificial Intelligence for Mental Health Centre for Autonomous and Intelligent Systems His research spans knowledge representation, semantic technologies, spatio-temporal reasoning, and AI applications in mental health. Recent work focuses on large language models for formal verification, defeasible reasoning, and compliance checking in legal contexts. He has contributed to qualitative spatial reasoning frameworks, temporal representation in OWL, and semantic IoT systems. Active in academic service as a programme committee member for IEEE conferences, he has published extensively on semantic web technologies, ontologies, and AI applications. His research fingerprint includes ontology engineering (100%), semantic web (66%), and temporal reasoning (15%) across 63 publications since 2009.

• 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.

• 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
• Knowledge Representation
• Automated Reasoning
• +3 more

Yuliya Lierler is a full Professor of Computer Science at the University of Nebraska Omaha (UNO), affiliated with the College of Information Science & Technology (IS&T). She holds the Cheryl Prewett Diamond Professorship since 2020 and received the Mentor of the Year Award in 2025. Her research focuses on artificial intelligence, particularly knowledge representation, automated reasoning, declarative problem solving, and natural language understanding. She co-directs the NLPKR lab and has authored over 70 peer-reviewed articles in top AI venues. Her books include Discrete Mathematics in a Nutshell and Digital Minimalism for Teens . Education: Ph.D. in Computer Science from the University of Texas at Austin (2010). Professional development includes training in AI-driven teaching methodologies and online education. Research Interests: She explores formal methods in AI, including logic programming semantics (e.g., Answer Set Programming), automated reasoning techniques, and applications in natural language processing. Her work bridges theoretical foundations with practical tools, such as the text2ALM information extraction system. Service & Leadership: Co-Chair of the 38th International Conference on Logic Programming (2022), Executive Committee member of the Association for Logic Programming (since 2020), and former Graduate Program Committee Chair (2018–2020). She has organized multiple international conferences and contributed to AI education initiatives. Awards: Recipient of the 2025 Mentor of the Year Award (Nebraska Women in Tech), 2024 Outstanding Research Award (IS&T College), and 2016 Best Student Paper Award (with Amelia Harrison). Labs & Teams: Co-director of the NLPKR lab, focusing on natural language processing and knowledge representation. Collaborates on projects integrating declarative programming with semantic understanding.

Andrea FormisanoView profile

Associate Professor

• Computational Logic
• Logic programming
• Answer Set Programming (ASP)
• +9 more

Andrea Formisano is an Associate Professor in Computer Science at the Department of Mathematics, Informatics and Physics (DMIF) at the University of Udine, Italy. His research spans diverse areas within computational logic, including logic programming, answer set programming (ASP), constraint logic programming (CLP), action languages, automated deduction, theory reasoning, set theory, relational reasoning, GPU computing, and non-classical logics. Contact : Via delle Scienze 206, 33100 Udine, Italy | Tel: +39 0432 558496 | Fax: +39 0432 558400 Teaching : Offers courses on Operating Systems and Programming on Parallel Architectures through the university's elearning platform. Research Keywords : Computational Logic, Logic programming, ASP, CLP, Action languages, Automated deduction, Theory reasoning, Set theory, Relational reasoning, GPU computing, Games, Non-classical Logics. Professional Affiliations : Active in academic events such as the International Conference on Logic Programming (ICLP), Italian Conference on Computational Logic (CILC), and the Association for Logic Programming (ALP). He is also affiliated with the Italian Association for Logic Programming (GULP).

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

Tomi Janhunen is a Professor in Computing Sciences at Tampere University, part of the Faculty of Information Technology and Communication Sciences. His expertise spans Artificial Intelligence, Logic Programming, and Theoretical Computer Science. He actively contributes to academic leadership roles, serving on boards of the Finnish Association of Computer Science and Finnish Artificial Intelligence Society. His research focuses on Answer Set Programming (ASP), probabilistic reasoning systems, explainable AI, and optimization techniques applied to cybersecurity and maintenance scheduling. Key grants include the XAILOG and AI-ROT projects funded by the Research Council of Finland. Notable achievements include three prestigious awards: Best Paper Awards at the European Conference on Logics in AI (2021) and International Conference on Logic Programming (2023), and the Harold Boley award for system description (2022). Dr. Janhunen’s work emphasizes practical applications of declarative programming paradigms. Recent projects include Plingo—a probabilistic ASP system—and cybersecurity compliance frameworks in DevSecOps environments. His contributions bridge theoretical advancements with real-world challenges in AI security and industrial optimization.

Carl CoreaView profile

Researcher

• Business Informatics
• Theoretical Informatics
• Artificial Intelligence
• +3 more

Dr. Carl Corea is a postdoctoral researcher at the University of Koblenz-Landau, Germany, affiliated with the Process Science Group within the Department of Computer Science. He holds a PhD in Computer Science (with distinction, 2020) and has served in roles such as Acting Professor of Business Information Systems (2023/24) at Justus Liebig University Giessen and Visiting Researcher at SAP Signavio. His research bridges business informatics and theoretical computer science, focusing on process mining, declarative process specifications, and decision modeling (DMN). He actively contributes to academic leadership roles, including memberships on doctoral committees, examination boards, and interdisciplinary research centers at the University of Koblenz. Corea's research interests include business process management, artificial intelligence applications in processes, and inconsistency measurement in business rules and process models. He has delivered courses on AI in Accounting, Project Management, and Business Process Management at multiple institutions. His work has been recognized with awards such as the Best Paper Award at WI 2019 and the Debeka Innovationspreis for research projects like 'Predictive Process Monitoring'. He serves on the program committees of major conferences in AI and business process management, including KR, AAAI, BPM, and ECAI. His publications span topics like declarative process modeling, DMN verification, and carbon-aware process execution. Corea also chairs Minitracks at events like HICSS and oversees conference organization for tracks such as Business Process Technology. Education: PhD in Computer Science (2020, with distinction) Awards: Multiple research and teaching awards, including nominations for early-career recognition Administration: Member of doctoral committees, academic boards, and interdisciplinary research centers Grants: DAAD Fellowship for international conference participation (2020)

William RegliView profile

Professor

• Artificial Intelligence
• Robotics
• Computational Modeling
• +9 more

William Regli is a Professor at the University of Maryland's Clark School of Engineering, holding appointments in Computer Science, Electrical and Computer Engineering, and the Institute for Systems Research. He also directs the Applied Research Laboratory for Intelligence and Security (ARLIS), overseeing over 75 researchers focused on defense and intelligence challenges. Regli's career spans academia, government leadership (including DARPA's Defense Sciences Office), and industry, with over 250 publications and five foundational U.S. patents in 3D CAD search. His research integrates AI, robotics, and computational modeling to address interdisciplinary problems in engineering, materials science, and national security. Education: Ph.D. and B.S. in Mathematics from the University of Maryland and Saint Joseph's University, respectively. He is a Fellow of AAAS and IEEE, recognized for contributions to 3D search and intelligent manufacturing. Research interests include AI agents, cyber-infrastructure for engineering data sustainability, advanced materials design, and robotic interoperability using category theory. His recent work emphasizes applying AI to national security, including trustworthy AI evaluation and social science integration. Awards include the DARPA Meritorious Public Service Medal (2018), AAAS Fellowship (2020), and IEEE Fellowship (2017). His articles reflect a focus on multi-agent systems, robotic task planning, and formal methods in autonomous systems. He advises multiple PhD students and has spun off two tech startups. Regli's laboratories include ARLIS, where he develops solutions for defense missions, and collaborates with the Maryland Robotics Center. His work bridges academia and government, emphasizing real-world impact through innovative computing research.

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Planning
• +3 more

Yannis Dimopoulos is a Professor and Department Vice-Chair at the Department of Computer Science, University of Cyprus. He holds a B.Sc. and Ph.D. in Computer Science from the Athens University of Economics (1987 and 1992, respectively). Prior to his current role, he held research positions at the Max-Planck-Institut für Informatik in Germany and the University of Freiburg. His research focuses on Artificial Intelligence , particularly in Knowledge Representation and Reasoning , Planning , Logic Programming , Constraint Satisfaction , and Machine Learning . He has published extensively in top conferences and journals, including AAAI, IJCAI, and Artificial Intelligence. Dimopoulos's work integrates theoretical contributions with practical applications, such as argumentation frameworks, planning systems, and multi-agent negotiation. His publications reflect a strong emphasis on formal methods, computational logic, and AI reasoning. He has advised numerous students and contributed to the development of tools like plasp for Answer Set Programming-based planning. His research has been supported by grants and collaborations with international institutions.

• Answer Set Programming
• Logic Programming
• Knowledge Representation
• +7 more

Mario Alviano is a Professor at the University of Calabria's Department of Computer Engineering, Modeling, Electronics and Systems (DIMES) in Rende, Italy. With a prolific publication record spanning from 2008 to 2025, he has established himself as a leading researcher in Answer Set Programming (ASP), logic programming, and knowledge representation. His work bridges theoretical foundations with practical applications across diverse domains including cybersecurity, environmental monitoring, and explainable AI. Alviano's research focuses on advancing the theoretical understanding and practical applications of Answer Set Programming. His key contributions include developing ASP Chef, a visualization and development framework for ASP; advancing theoretical foundations of conditional reasoning and typicality in weighted knowledge bases; and creating bridges between neural networks and symbolic AI through preferential interpretations. His recent work explores temporal extensions to conditional logics, applications of ASP to digital twin visualization, and tools for improving explainability in AI systems. Alviano's publications consistently appear in top-tier venues including ICLP, LPNMR, JELIA, and Theory and Practice of Logic Programming. His research demonstrates strong trends toward practical applications of theoretical advances, with increasing focus on explainability, visualization, and real-world problem solving. The recent surge in publications (26 in 2024 alone) indicates significant ongoing research activity and leadership in the field. His work increasingly integrates ASP with other AI paradigms, particularly neural networks, to create more interpretable and robust AI systems. Alviano has made substantial contributions to the development of tools and frameworks that lower barriers to entry for ASP, most notably ASP Chef which provides visualization capabilities for complex logic programs. His work on Hashcash Tree demonstrates applications to security problems, while his research on marketplace logistics shows practical business applications of declarative programming. His collaborative network is extensive, with frequent co-authorship with researchers including Wolfgang Faber, Nicola Leone, Francesco Ricca, Carmine Dodaro, Laura Giordano, and Daniele Theseider Dupré, reflecting strong connections across European AI research institutions. Alviano has also organized workshops including multiple editions of Datalog 2.0, demonstrating leadership in the logic programming community.

• Artificial Intelligence
• Knowledge Representation
• Constraint Answer Set Programming
• +4 more

Dr. Yuliya Lierler is a Professor in the Department of Computer Science at the University of Nebraska Omaha's College of Information Science & Technology. She has been a faculty member since 2012, reaching the rank of full professor, and was appointed to the Cheryl Prewett Diamond Professorship in 2020. Her work focuses on artificial intelligence, particularly in knowledge representation, automated reasoning, and declarative problem solving. PhD in Computer Science (University of Texas at Austin, 2010) Dr. Lierler's research bridges logic programming with practical AI applications, including natural language understanding, constraint satisfaction, and SMT-based solvers. She is a co-director of the NLPKR lab and has authored over 70 peer-reviewed publications in venues like Artificial Intelligence Journal and AAAI. Her contributions include open-access textbooks and tools like text2alm for semantic information extraction. Her recent publications explore advancements in answer set programming (ASP) semantics, automated reasoning frameworks, and hybrid knowledge representation systems. She has served as program co-chair for major conferences like ICLP (2022) and PADL (2017), and received awards such as the IS&T Outstanding Research Award (2024). Dr. Lierler also mentors students and leads initiatives in teaching innovation through online education and professional development programs. Mentor of the Year Award, Aksarben Foundation (2025) IS&T Outstanding Research and Creativity Award (2024) Best Student Paper Award (with Amelia Harrison, 2016) Dr. Lierler contributes to academic service through leadership roles in international conferences and program committees. Her lab, NLPKR, focuses on integrating natural language processing with formal logic, while her teaching emphasizes formal methods and AI foundations.

• 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.

• 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)

Michael GelfondView profile

Professor

• Knowledge Representation
• Logic Programming
• Answer Set Programming
• +3 more

Michael Gelfond is a Professor in the Department of Computer Science at the University of Texas at El Paso, affiliated with the Knowledge Representation Lab and the Texas Action Group. His research focuses on logic programming, knowledge representation, and non-monotonic reasoning, with significant contributions to Answer Set Programming (ASP) and the stable model semantics. M.S. in Mathematics, St. Petersburg University (1968) Ph.D. in Mathematics, Steklov Mathematical Institute (1974) His work bridges mathematical logic with AI, enabling intelligent agents to reason about dynamic domains. Recent publications explore A-Prolog for diagnostic reasoning, concurrent action effects, and declarative programming frameworks. He has received numerous accolades, including two Most Influential Paper in 20 Years Awards from the Association for Logic Programming, Fellowships from the European Academy of Sciences and AAAI, and the Burlington Northern Distinguished Achievement Award. His teaching includes courses on artificial intelligence, algorithms, and automata theory. Area Editor, Journal of Theory and Practice of Logic Programming Executive Editor, Journal of Logic and Computation Co-founder, Knowledge Representation Lab Co-chair, 27th International Conference on Logic Programming (2011)