Hello 🤗

I am a PhD candidate in Computer Science at the University of Leicester, supervised by Professor Reiko Heckel. My research focuses on graph machine learning, Deep Graph Transformation, Graph Neural Networks, benchmarking, and empirical model evaluation.

My PhD develops benchmark-first frameworks for graph-to-graph learning. I am interested in how graph transformation tasks should be defined, how model architectures should be compared, and how evaluation protocols can be made more reproducible across synthetic and real-world graph datasets.

Research interests

• Graph transformation learning: defining and evaluating graph-to-graph learning tasks.
• Benchmarking and reproducibility: designing shared experimental conditions for comparing model architectures.
• Graph Neural Networks and Graph Rewriting: studying how graph-structured learning systems can be made easier to specify, compare, and understand.
• Research software: building experimental pipelines for synthetic graph-computation tasks and real-world graph datasets.

Current status

My thesis submission is expected in September 2026, and I am interested in postdoctoral and teaching-and-research opportunities from October 2026.

You can find my publications, talks, teaching record, and CV using the links above. Please feel free to get in touch if you are interested in graph learning, graph transformation, benchmarking, or reproducible AI.