Published several papers including 'Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models' (NeurIPS 2025) and 'Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks' (ICML 2025).
Research Experience
Professional experience in research at Microsoft and Google, working on creating the next large Graph Foundation Model and studying the capabilities of LLMs in processing graph information.
Education
PhD candidate at the Computer Science Department, University of Oxford, supervised by Prof. Michael M. Bronstein and Prof. Ismail Ilkan Ceylan.
Background
Passionate researcher and PhD candidate at the University of Oxford, specializing in Geometric Deep Learning. Interested in exploring innovative solutions at the intersection of theory and application.