Dr Przemysław (Przemek) Wałęga

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 https://dblp.org/pid/152/3424.html

Please do not hesitate to contact me if you are interested in working on the above topics!

Publications

2023

2021