Donghwan Shin is a machine learning engineer and current 차세대 개발팀 매니저 with eight years of experience focused on computer vision and deep learning for real-time surveillance and security applications. He has led projects that span intrusion, loitering, fall and violence detection, mask and face verification, and X-ray object detection—improving a security model’s accuracy from 81% to 93% and earning KISA civilian certifications. Skilled in data refinement, model optimization, and deploying SoTA detection and tracking methods, he combines hands-on engineering with practical productization for CCTV and airport safety systems. A Google ML Bootcamp alumnus with a computer engineering background, he is quietly driven by R&D and routinely applies novel techniques to reduce noise and boost recognition in challenging video streams.
8 years of coding experience
5 years of employment as a software developer
학사, Computer Engineering, 학사, Computer Engineering at 한국항공대학교
Contributions:22 pushes, 1 branch in 1 year 11 months
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