David Tena Cucala

David Jaime Tena Cucala

Research Associate

Wolfson Building, Parks Road, Oxford OX1 3QD

Themes:

• Data and Knowledge

Interests

I work in the area of knowledge representation and reasoning, within the field of artificial intelligence. Currently my research is focused on three topics:

1. The design of reasoning algorithms for expressive Description Logics, particularly algorithms that are sound and complete, but also efficient and scalable. I have worked on the reasoners PAGOdA and Sequoia, which cover the logic behind the ontology language OWL 2 DL, a standard of the Semantic Web.  
2. The study of machine learning models based on logical rules. These models are straightforwardly interpretable, which helps verify their safety and compliance with fairness and transparency standards. I believe that rules can also provide effective inductive biases.
3. Logics for temporal reasoning, particularly in the intersection of Datalog with Metric Temporal Logics. 

For my broader interests, please see my personal website.

Biography

I studied Mathematics and Physics at Universitat Autònoma de Barcelona, from 2008 to 2013. I was originally interested in Astrophysics, but I became fascinated by metaphysical questions arising from modern physics. I applied for the MSt in Philosophy of Physics at University of Oxford in 2013, and I spent another year in the BPhil in Philosophy at the same university, studying Ethics and Philosophy of Science. My focus then shifted towards the question of how existing sources of knowledge can be aggregated to answer complex questions, like those of Philosophy. In 2015, I went on to study the MSc in Computer Science at the University of Oxford, with a focus on Knowledge Representation and Automated Reasoning. In 2016, I started a DPhil in Computer Science in the same area and research group, which I finished in 2020.

Selected Publications

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• Pay−as−you−go consequence−based reasoning for the description logic SROIQ

  David Tena Cucala‚ Bernardo Cuenca Grau and Ian Horrocks

  In Artif. Intell.. Vol. 298. Pages 103518. 2021.

  Details about Pay−as−you−go consequence−based reasoning for the description logic SROIQ | BibTeX data for Pay−as−you−go consequence−based reasoning for the description logic SROIQ | DOI (10.1016/j.artint.2021.103518) | Link to Pay−as−you−go consequence−based reasoning for the description logic SROIQ

• DatalogMTL with Negation Under Stable Models Semantics

  Przemyslaw Andrzej Walega‚ David J. Tena Cucala‚ Egor V. Kostylev and Bernardo Cuenca Grau

  In Meghyn Bienvenu‚ Gerhard Lakemeyer and Esra Erdem, editors, Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning‚ KR 2021‚ Online event‚ November 3−12‚ 2021. Pages 609–618. 2021.

  Details about DatalogMTL with Negation Under Stable Models Semantics | BibTeX data for DatalogMTL with Negation Under Stable Models Semantics | DOI (10.24963/kr.2021/58) | Link to DatalogMTL with Negation Under Stable Models Semantics

• Stratified Negation in Datalog with Metric Temporal Operators

  David J. Tena Cucala‚ Przemyslaw Andrzej Walega‚ Bernardo Cuenca Grau and Egor V. Kostylev

  In Thirty−Fifth AAAI Conference on Artificial Intelligence‚ AAAI 2021‚ Thirty−Third Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2021‚ The Eleventh Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2021‚ Virtual Event‚ February 2−9‚ 2021. Pages 6488–6495. AAAI Press. 2021.

  Details about Stratified Negation in Datalog with Metric Temporal Operators | BibTeX data for Stratified Negation in Datalog with Metric Temporal Operators | Link to Stratified Negation in Datalog with Metric Temporal Operators

Activities

• Machine Learning Systems
• Knowledge Representation and Reasoning