In my free time, I enjoy reading astronomy books, painting, and working as a voice actor for children's audiobooks on YouTube!
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Minseo (Sonia) Kim
I am a first year M.S. student in Electrical Engineering at Stanford University working in the Stanford Computational Imaging Lab, advised by Prof. Gordon Wetzstein.
I am broadly interested in developing computational imaging algorithms that tackle complex inverse problems across diverse scientific domains such as medical imaging, optical imaging, astronomical imaging, X-ray crystallography, and cryo-electron microscopy, leveraging AI tools like generative models and physics-informed neural networks to enhance reconstruction. I am passionate about bridging the gap between computational methods and real-world imaging challenges to advance scientific discovery.
I did my B.S.E. (Honors) in Electrical Engineering and Data Science with a minor in Mathematics at University of Michigan - Ann Arbor, where I was advised by Prof. Jeffrey Fessler.
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Dual Ascent Diffusion for Inverse Problems
Minseo Kim, Axel Levy, Gordon Wetzstein
under review, 2025
project page /
bibtex /
code (coming soon) /
arXiv
A diffusion model-based solver for inverse problems that is better, faster, and more robust to noise than relevant baselines.
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Machine Learning Models for Undersampled MRI Reconstruction
Minseo Kim, Jeffrey Fessler (capstone advisor)
B.S.E. Honors Capstone Project, 2024
poster /
bibtex /
code /
pdf
I implemented a score-based diffusion model with posterior sampling to reconstruct high-quality MRI images from undersampled k-space data, tested on over 3000 FastMRI dataset images.
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Interstellar Dust Scattering: Mathematical Modeling and Halo Intensity Calculations
Minseo Kim, Lia Corrales (capstone advisor)
B.S.E. Data Science Capstone Project, 2024
code /
pdf
Designed the double interstellar dust scattering physics model and developed mathematical proofs to derive halo intensity using analytic and numerical methods.
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PyTorch and Julia Software for Image Reconstruction
Minseo Kim, Jeffrey Fessler (advisor)
Software package development, 2023
doc /
julia /
pytorch
Implemented 2D branchless distance-driven forward projection and backprojection algorithm for computed tomography (CT) reconstruction using both PyTorch and Julia language.
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Research Intern
SLAC National Accelerator Laboratory, MLCV@LCLS
June 2025 -
Research in the area of computational structural biology focused on developing experiment-grounded protein structure generative models, with Doris Mai, Frederic Poitevin, and Prof. Matthias Kling.
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Digital Signal Processing Intern
Zoox, Inc., Advanced Hardware Engineering Team
May 2024 - August 2024
Worked on developing AI-powered audio mining systems and multimodal data processing pipelines, implementing models like PANN and AudioCLIP for text-based audio search and applying DSP techniques for vehicle data preprocessing, with Venkata Chebiyyam and Shaminda Subasingha.
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Contact me at kminseo@stanford.edu
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