United Kingdom
I am interested in the application of AI to improve diagnostic potential in major diseases, particularly in oncology and cardiology. Having leveraged computer vision and digital pathology in my research, I aim to combine these technical insights with my clinical background to enhance medical workflows.
● Completed the Rani Rawji Studentship at UCL Cancer Institute, correlating tumour ploidy with cell features using flow cytometry and digital pathology. ● Gained hands-on expertise in sample preparation, cytometric analysis, and gating strategies across ~100 tumour cases. ● Applied deep learning based image segmentation and Python scripting to extract nuclear features, generate ploidy estimations, and benchmark computational algorithms.
● Supported prospective medical students through seminars, personal statement guidance, and Q&A sessions ● Conducted one-to-one interviews and drop-in sessions, providing personalised feedback and academic advice ● Assisted in planning and coordinating daily activities, ensuring smooth delivery of the admissions programme
● Built an AI-powered Celonis dashboard to visualise medical student performance in CVC training ● Analysed time-to-event data and identified critical steps, applying predictive analytics to assess risk ● Presented actionable insights to Celonis to support improved training outcomes
● Provided one-to-one coaching for medical school applicants ● Guided students on applications, personal statements, and interviews ● Supported applicants, including those previously unsuccessful, to secure offers