Ziyuan Li
Graduate Researcher
Missouri, United States
Summary
🤩
Rockstar🎓
Top SchoolZiyuan Li is a Biomedical Engineering PhD candidate and graduate researcher at Washington University in St. Louis who applies machine learning, computational imaging, and experimental engineering to decode visual processing in mice. Over nine years of research experience, he has built Fourier-based retinotopic mapping pipelines, designed fluorescence imaging systems, and developed CNNs that reconstruct visual stimuli from neural activity. His work spans neuroscience and bioengineering—from cardiac MRI segmentation and 3D mesh reconstruction to cellular deconvolution and electrophysiology simulations—showing a talent for translating algorithms into experimental tools. An active contributor to open-source tensor learning (notably improving MPS decomposition stability and backend compatibility in TensorLy), he blends rigorous theory with practical implementation. Colleagues describe him as methodical and inventive, often creating novel pipelines that bridge data science and lab instrumentation.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Biomedical Engineering, Doctor of Philosophy - PhD, Biomedical Engineering at Washington University in St. Louis
Github Skills (8)
tensorrt10
machine-learning10
python10
decomposition10
linear-algebra9
tensor9
numpy8
algebra7
Programming languages (2)
Github contributions (5)
tensorly/tensorly
Sep 2018 - Sep 2018
TensorLy: Tensor Learning in Python.
Role in this project:
ML Engineer
ML EngineerContributions:20 commits, 2 PRs, 16 comments in 19 days
Contributions summary:Ziyuan primarily contributed to the `mps_decomposition_cross.py` file, which focuses on Matrix Product State (MPS) decomposition techniques within the context of tensor learning. Their commits involved bug fixes, code improvements, and adapting the code to work with different backends such as MxNet. They also addressed issues related to numerical stability and matrix operations, demonstrating a focus on the practical implementation of tensor decomposition methods.
tensor-factorizationtensor-decompositionpythontensor-learningtensor
zongyi-li/zongyi-li.github.io
Mar 2020 - Jan 2025
A beautiful Jekyll theme for academics
Contributions:120 pushes, 3 branches in 4 years 10 months
academicsbeautiful-jekylljekylljekyll-themebeautiful-jekyll-theme
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