Hi, I’m Eliot Wong-Toi, a PhD Candidate in Statistics at University of California, Irvine (UCI), advised by Stephan Mandt. I enjoy working at the intersection of statistical theory, machine learning, and applied data problems. My research centers on uncertainty quantification in regression and generative models, covering mean-variance regression, generative uncertainty, and conformal prediction. My work has been supported by a Hasso Plattner Institute Research Fellowship.
During my PhD, I have applied statistical and machine learning methods across diverse domains, including:
Before UCI, I received my BS in Mathematics–Computer Science (cum laude) from University of California, San Diego, where I worked in the Pulmonary Imaging Lab under Rui Carlos Pereira de Sá. There, I applied deep learning methods to medical imaging, developing tools to accelerate annotation and segmentation of imaging datasets.
I will complete my PhD in December 2025 and am currently seeking roles as an Applied Scientist or Data Scientist where I can combine methodological innovation with impactful applications.
University of California, Irvine, Irvine, CA
University of California, San Diego, La Jolla, CA
First-Author Publications
Co-Author Publications
Software