Mark Nishimura
PHD Candidate
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolMark Nishimura is a Stanford EE PhD candidate (expected 2023) with a decade of experience applying optimization and deep learning to computational imaging and 3D scene reconstruction. He has prototyped and validated deep learning solutions in industry settings at Apple and Meta, bridging simulation and real-world hardware for intrinsic imaging and search/retrieval tasks. His research blends convex optimization, compressive sensing, and learned models to push practical imaging pipelines from theory to implementation. Comfortable in C++, MATLAB, and modern ML toolchains, he has repeatedly turned academic ideas into working prototypes and diagnostic analyses. Based in Palo Alto, he pairs rigorous academic training with hands-on engineering instincts that surface subtle data failure modes and robustness fixes.
10 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Stanford University
Spanish, English, Japanese
Github Skills (29)
python10
cvxpy10
convex-optimization10
mathematical-optimization10
convex10
numerical-optimization10
embedded10
modeling10
optimization10
iterative7
mri6
argument-parsing6
dataclasses6
argparse5
effort5
Programming languages (4)
Github contributions (5)
computational-imaging/single_spad_depth
Aug 2020 - Sep 2020
Contributions:28 commits in 1 month
computational-imaging/spad_single
Sep 2018 - Jul 2020
Contributions:303 commits in 1 year 10 months
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