I’m a computer-vision engineer in the Machine Intelligence for Space Superiority (MISS) Lab at the U.S. Space Systems Command, where I develop physics-informed ML pipelines for space-domain awareness. My recent work spans learned PSF photometry, multispectral material segmentation, and NeRF-based radiometry, with results presented at AMOS, SPIE (ATI; Optics & Optoelectronics), and the International Astronautical Congress. I’ve built scalable, weather-robust photometry frameworks, explored adaptive Gaussian PSFs for high-precision satellite and stellar photometry, developed real-time multispectral segmentation methods, and investigated radiometry modeling with NeRFs and GAN-based super-resolution.

I earned a B.S. in Computer Science (AI) with a minor in Creative Writing (poetry) and an M.S. in Management Science & Engineering (Operations & Analytics) from Stanford University.

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