I'm Riya Shet, an MSc Health Data Science student at the University of Birmingham, based in Dubai. I am currently writing my dissertation with Dr. Le Zhang on brain-tumour segmentation.
Previously, I was a research associate at a psychiatry clinic, where I helped optimise the clinic's operations and patient experience through systems design. That work taught me that even strong ideas need the right infrastructure and institutional readiness before they can become part of care. I now bring that lesson into health data science, where my work combines clinical context, statistical modelling, and machine-learning practice.
I care about deployment. The projects I want to work on are the ones that make it out of a notebook and into responsible use. For a model to be ready for healthcare, strong test numbers are not enough: its risks need to be understood, its potential harms minimised, and its path to use supported by clinician trust, board sign-off, and regulatory clearance.
I also lean towards ambitious problems. Compute and tooling are improving quickly, and work that looked out of reach a few years ago is becoming tractable now. I think healthcare AI should be willing to aim at difficult problems, as long as that ambition is matched by careful evaluation, clinical grounding, and respect for the risks involved. That is why I keep returning to projects across image analysis, data governance, multi-omics, and oncology.