Uwe Schmidt
Machine Learning Consulting And Software Development at Freelance
Dresden, Saxony, Germany
Summary
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Rockstar🎓
Top SchoolUwe Schmidt is a machine learning consultant and software developer with 12 years of experience bridging academic research and production systems from Dresden, Germany. He holds a PhD in Computer Science and spent five years as a postdoc at the Max Planck Institute before moving into industry roles including Deep Learning Expert and CTO, now freelancing since 2020. Uwe contributes to prominent open-source imaging projects—improving StarDist’s multi-channel training and helping harden scikit-image’s relabeling and tests—demonstrating attention to robustness, edge cases, and build reliability. He combines deep algorithmic knowledge with practical engineering (OpenMP, packaging, CI/test automation), making him adept at taking research models into stable, production-ready code. An understated strength is his focus on data-type stability and overflow handling, which reduces failure modes in real-world image processing pipelines.
12 years of coding experience
7 years of employment as a software developer
Technischen Universität DarmstadtComputer Science, Computer Science at The University of British Columbia
Github Skills (15)
computer-vision10
scikit-image10
pytest10
python10
scientific-computing10
image-processing10
numpy10
test-automation10
testing10
object-detection9
tensorflow9
machine-learning9
openmp9
deep-learning9
keras9
Programming languages (9)
Github contributions (5)
stardist/stardist
Jun 2018 - Jan 2023
StarDist - Object Detection with Star-convex Shapes
Role in this project:
ML Engineer
ML EngineerContributions:28 releases, 58 reviews, 419 commits in 4 years 7 months
Contributions summary:Uwe focused on enhancing the model's performance by implementing improvements to the setup and processing. They worked on modifying the setup file to improve compiling with OpenMP and requiring a minimum Python version. They also addressed and fixed issues related to training and prediction with multi-channel images.
pytorchconvexobject-detectionstardistbioimage-analysis
scikit-image/scikit-image
Apr 2019 - Feb 2020
Image processing in Python
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:6 commits, 2 PRs, 21 comments in 10 months
Contributions summary:Uwe's contributions primarily involve fixing bugs and improving the `relabel_sequential` function within the scikit-image library. They have written and modified numerous test cases, focusing on edge cases, data type stability, overflow scenarios, and ensuring correctness across various inputs. The user has also refactored the testing setup and added more thorough checks within the tests.
image-processingpythoncomputer-visionimage
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