Research
Artificial Intelligence, Knowledge Representation and Reasoning, Temporal Reasoning, Logic, Computational Complexity, Graph Neural Networks
Interests
Artificial Intelligence (AI) and, in particular, Knowledge Representation and Reasoning (KRR) has quickly fascinated me and became the main source of my intellectual pleasure. My research is devoted to designing methods for reasoning, studying their computational properties, and developing efficient reasoning algorithms for them.
I am especially interested in methods for complex reasoning about time. Time is ubiquitous in our everyday lives, in the way we perceive and reason about the surrounding world, as well as how our AI algorithms do it. Consequently the topic of time brings together computer scientists, mathematical logicians, and philosophers, among others, providing a fascinating research area.
In the last years I worked intensively on theoretical foundations for the temporal reasoning languages. This includes the language of DatalogMTL, for which we established a number of complexity and expressiveness results. We have also introduced several practical reasoning algorithms and and developed a dedicated Metric Temporal Reasoning system MeTeoR.
Most recently, I am aim at bridging graph neural networks and logics, in the temporal setting. In particular, I am interested in characterising expressive power of temporal graph neural networks with logical languages and explain models' predictions with extracted logical rules.
At DBLP you can find a (probably) complete list of my publications
dblp.org/pid/152/3424.html
Please do not hesitate to contact me if you are interested in working on the above topics!
Publications

Publications of specific relevance to the Centre for Fundamental Computer Science
2024
Practical Reasoning in DatalogMTLWANG D, CUENCA GRAU B, WAŁȨGA PA and HU P
Theory and Practice of Logic Programming,
Cambridge University Press (Cup), 1-31.
28-10-2024
Rule-Based Temporal Reasoning: Exploring DatalogMTLWałęga PA
Leibniz International Proceedings in Informatics, LIPIcs. vol. 318
22-10-2024
Computational Complexity of Standpoint LTLDemri S and Wałęga PA
In
Ecai 2024,
Ios Press 16-10-20242023
Computing All Facts Entailed By An LTL SpecificationWałęga PA, Zawidzki M and Haase C
Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning., 679-689.
01-09-2023
The Stable Model Semantics of Datalog with Metric Temporal OperatorsWAŁĘGA PA, TENA CUCALA DJ, CUENCA GRAU B and KOSTYLEV EV
Theory and Practice of Logic Programming,
Cambridge University Press (Cup) vol. 24 (1), 22-56.
02-08-2023
Temporal Datalog with Existential QuantificationLanzinger M, Nissl M, Sallinger E and Wałęga PA
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence., 3277-3285.
01-08-2023
Stream reasoning with DatalogMTLWałęga PA, Kaminski M, Wang D and Grau BC
Journal of Web Semantics,
Elsevier vol. 76
01-04-2023
Finite Materialisability of Datalog Programs with Metric Temporal OperatorsWałęga P, Zawidzki M and Cuenca Grau B
Journal of Artificial Intelligence Research,
AI Access Foundation vol. 76
28-01-2023
Computational complexity of hybrid interval temporal logicsWałęga PA
Annals of Pure and Applied Logic,
Elsevier vol. 174 (1)
01-01-20232021
Subject-oriented spatial logicWałęga PA and Zawidzki M
Information and Computation,
Elsevier vol. 280
01-10-2021
Finitely Materialisable Datalog Programs with Metric Temporal OperatorsWałęga PA, Zawidzki M and Cuenca Grau B
Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning., 619-628.
01-09-2021
DatalogMTL with Negation Under Stable Models SemanticsWałęga PA, Tena Cucala DJ, Kostylev EV and Cuenca Grau B
Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning., 609-618.
01-09-2021