Summary
Jinyoung Kim is a Co-founder and CTO with a decade of experience translating academic computer vision and medical imaging research into FDA-cleared, production-grade systems for clinical decision support and real-time manufacturing inspection. He spans the full AI/ML lifecycle—from data pipelines and model development (PyTorch, TensorFlow) to cloud-native deployment and MLOps (Docker, Kubernetes, AWS/GCP)—and has led cross-disciplinary teams with clinicians and operators to run clinical studies and on-site pilots. His doctoral and postdoctoral work directly informed deployed tools for DBS targeting and electrode localization now used intra- and post-operatively, and he drove similar end-to-end efforts for PCB defect detection at his startup. Comfortable both as a hands-on engineer (Python/C++, OpenCV, ITK/VTK) and as a strategic founder, he combines regulatory experience (510(k) workflows) with practical productization instincts. Based in the Raleigh-Durham area, he quietly blends deep academic rigor with startup velocity, often surfacing niche technical fixes (like atlas outlier detection and adaptive histogram thresholding) that unlock clinical reliability.
8 years of coding experience
14 years of employment as a software developer
PhD ECE - computer vision machine learning and medical image computing, PhD ECE - computer vision machine learning and medical image computing at Duke University
MS ECE (minor: BME), MS ECE (minor: BME) at University of Minnesota
MS / BS ECE - signal and image processing, MS / BS ECE - signal and image processing at Hanyang University
Korean, English