Hi, I’m Clark Miyamoto!

I’m a first year PhD student at New York University’s Center for Data Science, advised by Eric Vanden-Eijnden & Joan Bruna. My research is on measure transport algorithms (e.g. diffusion, optimal transport) for scientific problems, particularly inverse problems and sampling, with a broader interest in computational statistics.

Before data science, I studied Physics. I transfered from the Physics PhD at NYU, and did my B.S. at the University of Southern California where I designed superconducting qubits under Eli Levenson-Falk.

Outside of work, I enjoy surfing, climbing, and taking photos.

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Some courses I’m taking right now: Intro to Data Science, Probability & Statistics, Mathematical Modeling using Data, and Intro to Analysis.