Research Interests
Currently in my PhD I am investigating neural methods for temporal prediction on structured data, with an emphasis on graph neural networks extensions. My overarching objective is to combine neural methods with symbolic AI approaches, and extract logical rules from the trained neural networks for making the predictions. In this way, the predictions can be understood by human experts, but the extraction is data-driven, making the best of the two AI paradigms.
Before my PhD I did research in Natural Language Processing, mostly in AMR (Abstract Meaning Representation) parsing - a type of semantic parsing.
Advertised Master Projects
- Dynamic link prediction and time prediction on temporal Knowledge Graphs
- Comparing trainability of Graph Neural Networks for logic-expressible functions