Jongchan Park
Staff Research Scientist at Lunit Oncology
Seoul, South Korea
Summary
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Rockstar🎓
Top SchoolJongchan Park is a Staff Research Scientist based in Seoul with a decade of experience applying deep learning to real-world problems, currently advancing AI in oncology at Lunit. He moved up from Research Scientist to staff leadership at the same company, combining research rigor from his KAIST master’s background with product-minded engineering. His open-source work includes maintaining the official PyTorch implementation of influential attention modules (BAM/CBAM) and integrating them into ResNet/ImageNet training pipelines, reflecting practical expertise in model training and attention mechanisms. Known for fixing tricky training bugs and tuning learning schedules, he bridges experimental research and production-ready model engineering.
9 years of coding experience
7 years of employment as a software developer
한국과학기술원(KAIST)
Github Skills (10)
attention-mechanism10
computer-vision10
pytorch10
resnet10
python10
imagenet9
shell8
script8
sh8
scripting8
Programming languages (5)
Github contributions (5)
Jongchan/attention-module
Oct 2018 - Sep 2022
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
Role in this project:
ML Engineer
ML EngineerContributions:17 commits, 2 PRs, 9 pushes in 3 years 11 months
Contributions summary:Jongchan primarily focused on modifications related to training scripts and model definitions within the attention-module repository. They corrected errors and updated the training procedure by modifying parameters such as resume paths, batch sizes, and learning rates. The user also integrated the CBAM and BAM attention modules into the ResNet architecture and updated the related scripts for ImageNet training. This indicates a focus on model training and experimentation with attention mechanisms.
pytorchconvolutionalcbambambottleneck
Jongchan/unsupervised_data_augmentation_pytorch
May 2019 - Jul 2019
Contributions:40 commits, 14 pushes in 1 month
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