Scott Sievert
Research Assistant at University of Wisconsin-Madison
Madison, Wisconsin, United States
Summary
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Rockstar🎓
Top SchoolScott Sievert is a research-focused machine learning engineer and PhD student at the University of Wisconsin–Madison with 11 years of engineering experience working at the intersection of large-scale ML, optimization, and systems. He develops and evaluates distributed optimization and active learning systems (including NEXT) under advisors Rebecca Willett and Robert Nowak, driven by a long-standing personal goal to push performance limits. His open-source contributions span high-profile scientific Python projects—Dask, SciPy, and scikit-image—where he improved parallel array handling, signal processing primitives, and wavelet denoising, plus practical ML examples and PyTorch interoperability fixes. Comfortable across theory, systems, and implementation, he blends rigorous testing and documentation with hands-on performance tuning. Based in Madison, WI, he brings deep academic grounding in ECE together with impactful community-facing work that eases large-scale ML development.
11 years of coding experience
University of Minnesota Twin Cities
Github Skills (28)
algorithms10
pytorch10
scipy10
lib10
set-operations10
operation10
python10
image-processing10
testing10
scikit10
machine-learning10
scikit-image10
array-merge10
numpy10
hyperparameter-optimization10
Programming languages (17)
Github contributions (5)
scikit-image/scikit-image
Jul 2016 - Oct 2019
Image processing in Python
Role in this project:
Data Scientist
Data ScientistContributions:22 commits, 10 PRs, 47 comments in 3 years 3 months
Contributions summary:Scott primarily contributed to the image processing library by implementing and refining wavelet denoising functionality. This involved adding a new `denoise_wavelet` function, writing tests, and creating an example demonstrating its use. The user also improved documentation, updated references, and made minor code improvements for better functionality and usability within the existing codebase.
image-processingpythoncomputer-visionimage
skorch-dev/skorch
May 2018 - Dec 2020
A scikit-learn compatible neural network library that wraps PyTorch
Role in this project:ML Engineer
ML EngineerContributions:3 reviews, 5 commits, 7 PRs in 2 years 7 months
Contributions summary:Scott contributed to the skorch library by addressing critical issues related to PyTorch version compatibility and model copying. They ensured the library correctly handled dependencies on specific PyTorch versions by enforcing version checks. Moreover, they addressed a bug related to the correct copying of model parameters, optimizer states and weights. The user also added a feature to disable callbacks to reduce overhead. They also added citation information to the documentation.
pytorchpythonwrapsneural-networksmachine-learning
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