Find Academic Supervisors

• Knowledge Representation
• Answer Set Programming
• Non-monotonic Reasoning
• +5 more

Pedro Cabalar is Full Professor at the Department of Computer Science of the University of Corunna, Galicia, Spain, and current coordinator of the inter-university Master in Artificial Intelligence (Universities of A Coruña, Santiago de Compostela and Vigo). He also serves as Area Editor (Theory Foundations) for Theory and Practice of Logic Programming and as Standard Editor for the Artificial Intelligence journal. Education: PhD in Computer Science, University of Corunna, 2001 Master in Computer Science, Politéchnic University of Madrid, 1993 Bachelor in Computer Science (3-year degree), University of Santiago de Compostela / University of Corunna, 1989 Research interests revolve around Knowledge Representation & Reasoning , especially Answer Set Programming , non-monotonic reasoning , temporal and modal logics , and causal reasoning . He investigates theoretical foundations (equilibrium logic, temporal extensions, deontic operators) and practical systems (telingo, eclingo, aspBEEF), with applications ranging from planning and diagnosis to explainable AI and healthcare decision support. His recent articles (2023-2025) exhibit a clear trend toward temporal and metric extensions of ASP , explainability , and hybrid reasoning systems , often combining logic programming with deontic or probabilistic features. Scientific awards & recognition: University of Corunna Dissertation Award, 2003 Best Paper Award at LPNMR 2019 Best Student Paper at ICLP 2020 Best Student Paper at JELIA 2019 Grants & projects: He currently leads or co-leads nationally funded Spanish projects (GEISER 2024-2028, ARLEKIN 2021-2024) and has coordinated EU COST actions (DigForASP) as well as earlier MINECO projects on temporal ASP and medical reasoning (TARDIS, MERLOT, FEAST, etc.). PhD supervision: He has successfully supervised three PhD theses (Martín Diéguez, Jorge Fandiño, Brais Muñiz) and continues to advise students within the Information Retrieval Laboratory (IRLab) and the Spanish node of Potassco Solutions.

• Logic Programming
• Answer Set Programming
• Non-monotonic Reasoning
• +3 more

Concepción Vidal Martín is an Associate Professor in the Department of Computer Science and Information Technology at the Faculty of Informatics, University of A Coruña (UDC). She has been evaluated for teaching merits over 6 five-year periods and for research merits over 4 six-year terms, demonstrating her long-standing commitment to both education and research in computer science. Her educational background, while not explicitly detailed in the provided text, includes a PhD as evidenced by her PDI (Profesor Doctor Interino) status and extensive research record. She has been actively contributing to academia since at least the late 1990s based on her publication history. Research Interests Dr. Vidal Martín specializes in Logic Programming , with a particular focus on Answer Set Programming and Non-monotonic Reasoning . Her research explores the Logical Representation of Knowledge and the theoretical foundations of equilibrium models in logic programming. She is a member of the Information Retrieval Lab research group at UDC, where she contributes to advancing knowledge in formal methods for artificial intelligence. Her work bridges theoretical computer science with practical applications in knowledge representation and reasoning systems. Through her publications in top-tier journals like Theory and Practice of Logic Programming and Artificial Intelligence , she has made significant contributions to the understanding of declarative programming paradigms and their applications in AI. Scientific Recognition Evaluation of teaching merits: 6 five-year periods Evaluation of research merits: 4 six-year terms Active researcher with consistent publication record since the late 1990s Principal investigator and collaborator on multiple national and regional research projects Academic Leadership Dr. Vidal Martín has supervised multiple master's theses, including "Solving Temporal Logical Programs with AI Planners" (2018/2019). She has been involved in numerous research projects funded by various entities including the State Research Agency (AEI), the Ministry of Science and Innovation, and the Galician Regional Government (Xunta de Galicia). Her research collaborations extend to international partners, as evidenced by her publications with researchers from various institutions. She has contributed to both theoretical foundations and practical applications of logic programming paradigms. Research Environment As a member of the Information Retrieval Lab at the University of A Coruña, Dr. Vidal Martín works within a vibrant research community focused on advancing knowledge in computer science, particularly in logical approaches to information processing and artificial intelligence. Her work contributes to the theoretical underpinnings of declarative programming languages and their applications in knowledge-intensive domains.

• Artificial Intelligence
• Machine Learning
• Network and Distributed Systems Management
• +3 more

Jorge Lobo is an ICREA Research Professor at the Department of Information and Communication Technologies at Universitat Pompeu Fabra (UPF) and holds a Visiting Professor appointment at Imperial College London's Department of Computing. He holds a Ph.D. in Computer Science from the University of Maryland (1990), an M.S., and B.E. from Simon Bolivar University. His career includes roles at IBM Research, Bell Labs, and academic positions at the University of Illinois at Chicago. His research focuses on AI, Network & Distributed Systems Management, Security/Privacy, and policy-driven systems. He pioneered policy-based network management, developing the PDL language and contributing to policy enforcement frameworks in telecommunication networks. His work spans policy languages (XACML, PMAC), role mining algorithms, and security policy analysis. He holds 7 patents in policy technologies and has authored two books with over 100 refereed publications. Key contributions: Policy-based systems, neuro-symbolic learning, privacy-preserving frameworks, and declarative distributed computing Notable achievements: ACM Distinguished Scientist, IBM Identity Management Product implementations Recent publications (2020-2024) emphasize neuro-symbolic learning, federated learning frameworks, differential privacy, and AI-driven security solutions. His work bridges formal logic with machine learning to create interpretable systems for complex challenges in network management and policy enforcement. Labs/Teams: Active in UPF's Artificial Intelligence and Machine Learning group. Collaborates internationally on policy-aware systems and declarative networking architectures.

Juan Carlos LópezView profile

Professor

• Embedded System Design
• Distributed Computing
• Advanced Communication Services
• +7 more

Juan Carlos López is a Professor of Computer Architecture at the University of Castilla-La Mancha (UCLM), where he has been employed since 1999. He previously served as Dean of the School of Computer Science from 2000 to 2008 and is currently the Director of the Indra Chair at UCLM. He is also Head of the ARCO (Computer Architecture and Networks) Group. Dr. López received his MS and Ph.D. degrees in Telecommunication (Electrical) Engineering from Technical University of Madrid in 1985 and 1989, respectively. From September 1990 to August 1992, he was a Visiting Scientist in the Department of Electrical and Computer Engineering at Carnegie Mellon University. From 1989 to 1999, he served as an Associate Professor of Electrical Engineering at Technical University of Madrid. His research activities center on embedded system design, distributed computing, and advanced communication services. His work spans Internet of Things (IoT), edge computing, computer vision applications, and health monitoring systems. He has co-founded a startup company focused on control and communication systems for metropolitan transportation, serving as CTO from 1992 to 1997. Analysis of his recent publications (2023-2025) reveals a strong focus on practical edge computing applications, particularly in agriculture (olive fly detection) and healthcare (fall detection for elderly). His work demonstrates expertise in FPGA-based hardware acceleration, IoT context reasoning, and astronomical instrumentation. His research bridges theoretical computer architecture with real-world applications in smart cities, precision agriculture, and assistive technologies for aging populations. Member of IEEE, ACM and ATI professional organizations Spanish Representative at IFIP TC10 (Computer Systems Technology) Dr. López has led numerous national and international projects funded by EU, NATO, and private companies including Indra and Telefónica. His Indra Chair position since 2006 demonstrates sustained industry collaboration. He has served on panels for the Spanish National Science Foundation and Ministry of Education and Science regarding Information Technologies research programs. From 2004 to 2009, he coordinated the Doctoral Education Program of the Ministry of Science and Innovation in the area of Information Technologies. He directs the ARCO Research Group, which focuses on Computer Architecture and Networks, with particular emphasis on embedded systems, energy-efficient computing, and IoT applications. His team has developed innovative solutions for smart cities, healthcare monitoring, and precision agriculture, often leveraging FPGA technology for hardware acceleration.

Carlos D. BarrancoView profile

Professor

• Computational Intelligence
• Fuzzy Logic
• Soft Computing
• +7 more

Carlos D. Barranco is a Professor at Universidad Pablo de Olavide , Spain, with over two decades of experience in Computational Intelligence , Fuzzy Logic , and Soft Computing . His work focuses on applying these techniques to Big Data , Flexible Querying , and Imperfect Information Management in databases. He teaches courses in Computer Science at both bachelor's and master's levels, including Advanced Programming , Big Data , and Data Analysis in Digital Humanities . Research interests include: Fuzzy Database Systems : Developing indexing strategies for possibilistic and fuzzy numerical/temporal data to improve query efficiency in traditional RDBMS. Big Data Applications : Leveraging fuzzy logic in bioinformatics, energy consumption forecasting, and medical image retrieval. Interdisciplinary Work : Bridging computational methods with Digital Humanities (e.g., medieval charter databases) and Medical Imaging . Collaborations span institutions across Spain and Europe, with publications in journals like Applied Soft Computing , International Journal of Intelligent Systems , and IEEE Transactions on Fuzzy Systems . His work has been presented at major conferences including IWBBIO , FUZZ-IEEE , and Flexible Query Answering Systems . Contact: cdbargon@upo.es

• Artificial Intelligence
• Health Informatics
• Multi-Agent Systems
• +3 more

Ignasi Gomez Sebastia is a researcher in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB). He holds a PhD and specializes in Artificial Intelligence applied to healthcare, multi-agent systems, and social network analysis. His work focuses on developing intelligent systems for healthcare support (e.g., LactApp for breastfeeding), agent-based models for elderly care, and smart city technologies for mobility optimization. Key contributions include frameworks like NoMoDEI for norm monitoring in electronic institutions and research on spatio-temporal patterns in location-based social networks. He actively collaborates with groups such as KEMLG and IDEAI-UPC, contributing to projects like SUstainable and PERsuasive Human Users mobility (SUPErHUB) and the AVICENA elderly healthcare initiative. His research spans over 30 publications since 2008, covering topics from mHealth applications to agent-oriented organizational modeling. He has led or participated in competitive R+D+i projects focusing on healthcare technology, smart cities, and AI-driven solutions for SMEs. His work bridges theoretical AI advancements with practical implementations in health, urban systems, and collaborative environments.

• Natural Language Processing
• Data Management
• Entity Resolution
• +4 more

Lucian Popa is a Principal Research Scientist at IBM Research - Almaden, leading a team developing human-in-the-loop systems to scale NLP technologies for diverse users and applications. His work integrates human intelligence, data, and machine learning to advance transparent, data-driven AI systems. His research spans Natural Language Processing, Data Management, and Explainable AI, with seminal contributions to schema mapping, data exchange, and entity resolution. He pioneers active learning frameworks that enhance human-AI collaboration for entity linking and annotation efficiency, focusing on making AI systems accessible in low-resource settings. Recent publications reveal a cohesive trajectory toward human-centered AI, emphasizing explainability in text understanding, entity resolution, and misinformation detection. His work consistently addresses real-world challenges through hybrid intelligence frameworks that balance automation with human expertise across financial, scientific, and social domains. Scientific recognition includes: Alonzo Church Award for Outstanding Contributions to Logic and Computation (2020) Test-of-Time Awards at ICDT, PODS, and EDBT conferences ACM Distinguished Member designation While no formal students or major grants are documented in public sources, Popa directs IBM research initiatives including the HIL framework for entity resolution and AutoAI for text. His team actively develops products like Global Table Extraction (GTE) that transform document processing through visual-context-aware AI. At IBM Almaden, he collaborates with researchers including Ron Fagin and Marina Danilevsky to bridge theoretical computer science with practical NLP applications, maintaining leadership in knowledge-intensive AI system design.

• Constraint Logic Programming
• Answer Set Programming (ASP)
• Stream Data Analysis
• +3 more

Joaquín Arias is an Associate Professor at the Universidad Rey Juan Carlos (URJC) in Madrid, Spain, since 2025. He previously served as an Assistant Professor at URJC (2020–2025) and as a Pre-Doctoral Researcher at the IMDEA Software Institute (2013–2020). He holds a Ph.D. in Computer Science (2020), a Master of Science in Computer Science (2015), a Bachelor of Science in Computer Science (2014), and a Master of Architecture (2002), all from the Universidad Politécnica de Madrid (UPM). His research focuses on constraint logic programming, answer set programming (ASP), and their applications in stream data analysis, spatial reasoning, and legal reasoning systems. His main research interests include (Constraint) Logic Programming, TCLP, s(CASP), and value-aware systems. He has developed frameworks like Modular TCLP and ATCLP for constraint integration and aggregate computation. Notable projects include applying s(CASP) to legal reasoning (s(LAW)), BIM modeling, and automated conversational agents using LLMs and ASP. His work emphasizes explainable AI and ethical alignment in automated decision-making. Key contributions include the Automated Legal Reasoning with Discretion framework (2024), a socialbot leveraging LLMs and ASP (2024), and a legal reasoning system for administrative processes (2024). He has contributed to proceedings of the ICLP workshops and edited volumes for conferences like AAAI and CAEPIA. His academic awards include the Best Paper Prize at CAEPIA 2021. Collaborations include the University of Texas at Dallas (2017), Aalto University (2019), and IMDEA Software Institute. His teaching includes promoting logic programming in computer science curricula, as highlighted in his 2023 SIIE conference paper.