My research interests are broadly in the fields of (Mechanistic) Interpretability and Graph Neural Networks. I am also a member of the WISDOM consortium, developing predictive models for complex diseases (in particular multiple sclerosis). However, the underlying motivation of understanding the inner workings of neural networks stretches pretty much across all fields, so feel free to about anything that interests you.
Recursive Algorithmic Reasoning Jonas Jürß,
Dulhan Jayalath,
and
Petar Veličković
✨ Oral:
In Proceedings of the Second Learning on Graphs Conference (LoG), PMLR 231, 2023
Rethinking Test Generalisation In Neural Algorithmic Reasoning
Manasvi Aggarwal,
Dulhan Jayalath,
and
Jonas Jürß
In The Fourth Learning on Graphs Conference (LoG, Extended Abstracts Track), 2025
Everybody Needs a Little HELP: Explaining Graphs via Hierarchical Concepts Jonas Jürß,
Lucie Charlotte Magister,
Pietro Barbiero,
Pietro Liò,
and
Nikola Simidjievski
In NeurIPS Workshop: New Frontiers in Graph Learning, 2023