Biomedical data science today requires a combination of domain expertise and big picture vision that is crucial for the translation of scientific inquiries into actionable clinical solutions.
Over my career, I have worked on a number of trans-disciplinary research areas and have used scientific computing to make impactful contributions in physics, mathematics, and neuroscience. My current focus is on applying Machine Learning methods to enable scientific excellence in biomedical imaging and clinical practice.
As a senior Machine Learning specialist at UCSF’s Center for Intelligent Imaging, I help develop, train, and deploy pipelines that combine natural language understanding and machine vision to complement clinicians’ examination workflows, improving speed, reproducibility, and diagnostic reliability.
Previous work: As an applied data scientist at the Brain Networks Lab @ UCSF I worked towards understanding the mechanisms behind neurodegeneration, with the ultimate goal of improving prognostics and patient care.
Prior to working as a data scientist, I was a computational materials engineer at The Glotzer Lab @ the U of Michigan, and an experimentalist, synthesizing nano devices out DNA at The Douglas Lab @ UCSF.
I love meeting new people so feel free to drop me a message.