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• Artificial Intelligence
• Formal Methods
• Neuro-Symbolic AI
• +4 more

Andreas Brannstrom is a Postdoctoral Fellow at the Department of Computing Science, Umeå University, Sweden, conducting research on formal and neuro-symbolic methods for trustworthy, human-centered artificial intelligence. His work spans theoretical foundations in knowledge representation to applied verification of interactive systems and intelligent decision support. His research focuses on formal verification of human-agent interaction, neuro-symbolic AI integration, and ethical AI development. Key methodologies include Answer Set Programming (ASP), formal argumentation, and Description Logic (DL), targeting applications in deception detection, computational empathy, and behavior-change systems. Recent work emphasizes security in information-seeking dialogues and socio-technical aspects of AI deployment. Analysis of his 2023-2025 publications reveals a dominant trend in verifying social engineering vulnerabilities through formal methods, with significant contributions to machine ethics ontologies and multicultural affective computing. His research consistently bridges theoretical AI frameworks with real-world applications in healthcare, industrial logistics, and public safety. Brannstrom is affiliated with Umeå University's Agents and Reasoning Group, Formal Methods for Trustworthy Hybrid Intelligence, and Responsible Artificial Intelligence research groups. His active projects include "Strategic Argumentation to deal with interactions between intelligent systems and humans" (2020-2024) and "Collaborative mixed-reality aid for children with autism" (2019-2020), demonstrating commitment to socially impactful AI research.

João LeiteView profile

Professor

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Neuro-symbolic Artificial Intelligence
• +3 more

João Leite is a Professor of Computer Science at the Department of Computer Science, NOVA School of Science and Technology, NOVA University Lisbon. His career spans roles as Head of Department, Vice President of APPIA, Principal Investigator of the Intelligent Systems Group at NOVA LINCS, and Senior Visiting Fellow at CSE, UNSW, Sydney, Australia. He is an International Partner of Potassco Solutions and a member of IFIP TC-12 Artificial Intelligence. João's research focuses on Artificial Intelligence , Knowledge Representation and Reasoning , Neuro-symbolic AI , Answer-Set Programming , Argumentation Theory , and Multi-Agent Systems . 2002 : PhD in Computer Science, NOVA University Lisbon 1997 : MSc in Computer Science, NOVA University Lisbon 1994 : BSc in Electronic Engineering, University of Coimbra João's articles demonstrate a consistent focus on Answer-Set Programming (ASP), with applications in Knowledge Forgetting , Modular Reasoning , and Hybrid Knowledge Bases . His work bridges ASP with Ontologies , Multi-Context Systems , and Neural Networks , emphasizing Explainable AI and Dynamic Knowledge Evolution . Recent papers explore Provenance in Heterogeneous Systems , Efficient Reasoning with Intensional Concepts , and Stream Reasoning using neural architectures. Scientific Awards : Senior Visiting Fellow at CSE, UNSW, Sydney Award-winning collaborative project: The Politics of constraints: Discursive strategies in a three-level game João has led significant research projects such as FORGET (2018-2022) on information forgetting and RIVER (2018-2022) on knowledge-stream integration. He contributed to NEURASPACE (2022-2025) and Knowledge-Aware Cyber-Physical Systems (2015-2019). His software developments include NoHR (Hybrid Reasoning), EVOLP (Evolving Logic Programs), and SWARG (Social Abstract Argumentation Tool).

• Computer Science
• Artificial Intelligence
• Logic Programming
• +7 more

Stefania Costantini is a Professor in Computer Science with a focus on logic programming, multi-agent systems, and healthcare applications. She has contributed to the development of intelligent ecosystems for patient monitoring, ontology frameworks for medical wearables, and formal verification methods for agent systems. Research Interests: Logic-based agent modeling Complex event processing Healthcare technology integration Temporal and metalevel logic applications Wearable device classification Recent Article Trends: Stefania's work combines artificial intelligence with biomedical engineering, emphasizing real-time data analysis from wearables, noise pollution mitigation, and agent-based healthcare systems. Her publications show a consistent focus on computational logic foundations applied to practical healthcare scenarios. Collaboration Network: Key co-authors include Lorenzo De Lauretis, Fabio Persia, and C. Bertoncelli across interdisciplinary projects blending computer science with medical research.

• Answer Set Programming
• Logic Programming
• Artificial Intelligence
• +5 more

Carmine Dodaro is an active researcher in Answer Set Programming (ASP) at the University of Calabria's Department of Mathematics and Computer Science. With over 130 publications from 2011-2025, his work bridges theoretical advances in logic programming with practical healthcare applications. His primary research interests include: Answer Set Programming theory and implementation Compiler techniques for ASP solvers Healthcare scheduling optimization (operating rooms, nurse staffing, chemotherapy) Integration of ASP with other AI paradigms Real-world constraint satisfaction problems Dodaro's recent work demonstrates exceptional focus on healthcare applications of ASP, with multiple 2023-2024 publications addressing nurse scheduling, operating room management, rehabilitation planning, and nuclear medicine scheduling. His approach typically involves developing specialized ASP encodings that handle complex real-world constraints while maintaining computational efficiency. He maintains a highly productive collaboration network, particularly with Marco Maratea (52 co-authored papers), Mario Alviano (40), and Giuseppe Galatà (23), forming one of Italy's leading ASP research groups. His publications appear consistently in top venues including Theory and Practice of Logic Programming, IJCAI, AAAI, and specialized logic programming conferences. Dodaro has contributed significantly to both theoretical foundations (unsatisfiable core analysis, paracoherent reasoning) and practical implementations (WASP solver extensions, CNL2ASP translation tools). His 2024-2025 publications indicate ongoing research momentum with no signs of reduced activity.

• Artificial Intelligence
• Artificial Neural Networks
• Information Systems
• +3 more

Konstantin Schekotihin is an Associate Professor at the Department of Artificial Intelligence and Cybersecurity, Alpen-Adria University of Klagenfurt. His research focuses on artificial intelligence, machine learning, and semantic technologies with applications in industrial systems and semiconductor manufacturing. Reinforcement learning for industrial scheduling Answer Set Programming (ASP) and stream reasoning Failure analysis automation and ontology engineering Neuro-symbolic AI integration Knowledge-based systems in manufacturing Recent publications emphasize AI-driven optimization in semiconductor production, decomposition strategies for scheduling problems, and multi-agent systems for workflow management. His work combines symbolic reasoning with machine learning to address complex industrial challenges. Contact: Konstantin.Schekotihin@aau.at