Bernardo Cuenca Grau
Professor Bernardo Cuenca Grau
Room
305,
Wolfson Building,
Parks Road, Oxford OX1 3QD
United Kingdom
Interests
My research is in the broad field of artificial intelligence. In particular, my work revolves around the areas of knowledge representation and reasoning, knowledge graphs, computational logic, semantic technologies, and graph representation learning. My activities within these areas cover a wide spectrum, including theory and foundations, algorithm design, software and systems, technology standards, and engagement with industry
You can find my DBLP entry here and my Google Scholar profile here. You can also find my full CV here.
Biography
I am a professor at the Department of Computer Science and a Tutorial Fellow at Keble College. Until October 2017, I held a prestigious University Research Fellowship awarded by the British Royal Society. I was a co-founder of Oxford Semantic Technologies , a start-up company from the University of Oxford focusing on high-performance reasoning and query evaluation over large-scale knowledge graphs; the company was acquired by Samsung Electronics in July 2024.
Awards and Fellowships
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Distinguished Paper Award at the 2017 International Joint Conference on Artificial Intelligence for the paper "Foundations of Declarative Data Analysis Using Limit Datalog Programs"
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Best Paper Award at the 2010 AAAI Conference on Artificial Intelligence for the paper "How Incomplete is your Semantic Web Reasoner?"
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The 2021 Semantic Web Science Association 10 Year Award for the paper "LogMap: Logic Based and Scalable Ontology Matching".
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Best Paper Award at the 3thrd European Semantic Web Conference (ESWC-2006) for the paper "Repairing Unsatisfiable Concepts in OWL Ontologies."
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Royal Society University Research Fellowship (2009-2017).
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Oxford Department of Computer Science Teaching Award in 2021 and teaching commendation in 2022 for the course "Artificial Intelligence".
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University of Oxford Mathematical And Physical Sciences Division (MPLS) Commercial Impact Award (Honourable Mention) in 2021.
Doctoral Study in Computer Science
Students working towards their D.Phil (PhD) are an integral part of the Information Systems Group, and make a vital contribution to our research. See our studentships page for further details, and information about funding opportunities . Should you consider applying for a doctoral position in our group, please do not hesitate to contact me first.
Selected Activities
- Co-founder, Oxford Semantic Technologies.
- Editorial Board Member, ACM Transactions on the Web.
- Editorial Board Member, Transactions on Graph Data and Knowledge.
- Editorial Board Member, Semantic Web Journal.
- General Chair: 2020 International Workshop on Description Logics (DL-2020)
Software Tools
I have been involved in the design of several tools for ontology management and reasoning. These include the ontology matching tool LogMap , the ontology reasoners MORe , PAGOdA , and SEQUOIA, the temporal reasoner METEOR, and the semantic faceted search system SemFacet
See also
Selected Publications
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Bridging Max Graph Neural Networks and Datalog with Negation
David Tena Cucala and Bernardo Cuenca Grau
In Proceedings of the 21st International Conference on the Principles of Knowledge Representation and Reasoning (KR−2024). 2024.
Details about Bridging Max Graph Neural Networks and Datalog with Negation | BibTeX data for Bridging Max Graph Neural Networks and Datalog with Negation
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MTLearn: Extracting Temporal Rules Using Datalog Rule Learners
Dingming Wang‚ Przemyslaw Walega and Bernardo Cuenca Grau
In Proceedings of the 21st International Conference on the Principles of Knowledge Representation and Reasoning (KR−2024). 2024.
Details about MTLearn: Extracting Temporal Rules Using Datalog Rule Learners | BibTeX data for MTLearn: Extracting Temporal Rules Using Datalog Rule Learners
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Relational Graph Convolutional Networks Do Not Learn Sound Rules
Matthew Morris‚ David Tena Cucala‚ Bernardo Cuenca Grau and Ian Horrocks
In Proceedings of the 21st International Conference on the Principles of Knowledge Representation and Reasoning (KR−2024). 2024.
Details about Relational Graph Convolutional Networks Do Not Learn Sound Rules | BibTeX data for Relational Graph Convolutional Networks Do Not Learn Sound Rules