Taehoon Lee
Machine Learning Engineer at SK Telecom
Seoul, Korea, Republic of
Summary
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RockstarTaehoon Lee is a Machine Learning Engineer based in Seoul with 11 years of experience specializing in computer vision and MLOps. He is an active open-source contributor with substantive fixes and quality improvements to high-profile projects such as Keras, Keras Applications, scikit-learn, and the XLA compiler, demonstrating deep familiarity with model implementations and ML tooling. Taehoon’s contributions focus on bug fixes, backend compatibility, and documentation quality—work that improves reliability across TensorFlow/Theano backends and production model weight handling (e.g., ResNet50, NASNet). Comfortable across both research-facing libraries and low-level compiler code, he brings a pragmatic eye for robustness and reproducibility in ML systems. Colleagues can expect a detail-oriented engineer who elevates projects by tightening tests, clarifying docs, and polishing core code paths that many teams and deployments depend on.
11 years of coding experience
Github Skills (32)
c-language10
python10
data-science10
scikit10
testing10
machine-learning10
cntk10
keras10
tensorflow10
deep-learning10
resnet10
scikit-learn10
neural-network10
xla10
compiler10
Programming languages (7)
Github contributions (5)
keras-team/keras-applications
Jun 2018 - Nov 2019
Reference implementations of popular deep learning models.
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 45 commits, 37 PRs in 1 year 5 months
Contributions summary:Taehoon primarily contributed to the Keras applications repository by fixing bugs and improving the functionality of pre-trained deep learning models, particularly NASNet and ResNet50. Their commits focused on resolving issues related to model shapes, performance, and testing, and also included updates to model architectures and weights. Furthermore, the user addressed errors related to specific backends such as CNTK and Theano, ensuring compatibility and stability.
pytorchimplementationsdeep-learningkeras-neural-networkstheano
keras-team/keras
May 2017 - Jul 2019
Deep Learning for humans
Role in this project:ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:163 commits, 264 PRs, 32 pushes in 2 years 2 months
Contributions summary:Taehoon primarily contributed to the Keras library by addressing bugs, fixing typos, and improving the code's overall quality. The commits involved correcting errors in TensorFlow and Theano conversions for various convolutional layers, including Conv1D and ImageNet weight loading for ResNet50, and adding warnings for redundant outputs. Furthermore, the user focused on cleaning up docstrings and fixing typos across several core files and examples, particularly in applications like VGG and ResNet.
pythondata-sciencedeep-learningneural-networksmachine-learning
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