Jay Lee
AI Research Engineer - Team Lead at Lunit Cancer Screening
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolJay Lee is an AI research engineer and team lead with nine years of experience building high-throughput, mission-critical ML systems and production inference engines. He bridges research and engineering, having optimized Lunit’s CXR and MMG inference pipelines (up to 2.4x runtime and 31x postprocessing improvements) and led deployment-focused R&D that preserved model accuracy while drastically improving speed and reliability. Formerly a senior ML engineer at Deeping Source, he cut costs and boosted EdgeTPU performance with novel detection architectures and automation that eliminated onsite deployments. Jay’s open-source contributions (yolov5, torch2trt, DeepStream-Yolo) and personal tools (pt2keras, decko) reflect a practical focus on exportability and inference robustness, including automated verification for PyTorch→ONNX fidelity. Trained at Seoul National University’s data mining lab, he blends deep learning research—especially anomaly detection and data mining—with pragmatic system design and a knack for simplifying complex production workflows.
9 years of coding experience
9 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Seoul National UniversityUNSW Sydney
Stackoverflow
513reputation
11kreached
21answers
9questions
Github Skills (43)
pytorch10
yolov510
python10
classification10
image-classification10
tensorrt10
packaging10
inference10
onnx10
coreml10
resolver10
jetson-xavier10
instance-segmentation10
object-detection10
computer-vision10
Programming languages (5)
Github contributions (5)
JWLee89/The-Coding-Delight
Mar 2018 - May 2018
All source code from blog posts made on thecodingdelight.com will be uploaded here
Contributions:6 commits, 251 pushes, 1 branch in 2 months
JWLee89/FairMOT
Apr 2021 - Apr 2021
Contributions:251 pushes in 11 days
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