Experience

Working at the intersection of clinical NLP and applied AI research, developing systems that support decision-making in regulated healthcare environments. My focus is on knowledge-grounded LLM pipelines, information extraction from unstructured medical records, predictive modelling for hospital operations, and building auditable AI for regulated settings.

PhD research on knowledge representation and NLP. Worked on named entity recognition and relation extraction using Transformer and LLM architectures, knowledge graph construction and link prediction, and adverse drug event detection and medical concept normalisation.

Applied graph-based machine learning to real-world problems. Worked on anomaly detection on large-scale financial networks for government tax fraud investigation, and fault pattern recognition on event-sequence data from aerospace flight systems.