About Me
Hey there, welcome! I’m a PhD student in the Department of Biostatistics and Health Informatics, part of the Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King’s College London, where I am advised by Professor Richard Dobson, Dr Alfredo Iacoangeli, Professor Honghan Wu, Dr Chris Tomlinson and Dr Zhi Yao.
Previously, I’ve worked both across the academia, public healthcare and the start-up world. I completed my MSc in Clinical Neuroscience at the Institute of Neurology at University College London, and my BSc in Biomedical Science at the Univeristy of Brighton.
Research Interest
My research focuses on the intersection of machine learning, health informatics, and neurodegenerative diseases. Specifically, I aim to use Electronic Health Records (EHRs) and multimodal data to model the onset and progression of Motor Neurone Disease (MND) / Amyotrophic Lateral Sclerosis (ALS). My work involves developing computational approaches that integrate diverse data types—including clinical records, imaging, and genetic data—to better understand disease trajectories. Broadly, my research seeks to contribute to the early detection, monitoring, and treatment of neurodegenerative diseases through data-driven insights.
In the past, I have worked on a range of projects at the intersection of technology, healthcare, and user experience. This includes contributing to research on improving chest X-ray analysis by combining vision and language models with eye gaze patterns. I have also been part of a study exploring neck collar preferences and user experiences in motor neuron disease, looking at how well current outcome measures work for these devices. Additionally, I have worked on biomedical knowledge curation, including a scoping review on the use of knowledge graphs in healthcare and benchmarking approaches like in-context learning, fine-tuning, and supervised learning for curating chemical entities of biological interest (ChEBI).
News
- [October 2024] - Awarded the DRIVE-Health studentship and started on the EPSRC Centre for Doctoral Training in Data-Driven Health (DRIVE-Health) Centre for Doctoral Training.
- [October 2024] - Part of the organising team for the Foundation Models For Medical Imaging (FOMMIA) tutorial at MICCAI 2024.
- [August 2024] - Presented the work titled “Benchmarking and Analyzing In-context Learning, Fine-tuning and Supervised Learning for Biomedical Knowledge Curation: a focused study on chemical entities of biological interest” at the International Workshop on LLM+KG: Data Management Opportunities in Unifying Large Language Models+Knowledge Graphs