Jun Liu is Head of AI R&D with 11 years of experience building and delivering AI-driven medical imaging solutions across detection, segmentation, classification, and multi-modal fusion. He leads cross-functional teams to productionize algorithms that integrate with clinical systems (DICOM/PACS) and regulatory workflows, while championing MLOps, CI/CD, and agile practices tailored for healthcare. Prior roles span hands-on algorithm development at Infervision and Li Auto and competitive success on Kaggle—including top-5 placement in MICCAI2025 MBH-Seg—demonstrating both research depth and applied skill. Jun combines a strong academic background in applied statistics with practical experience optimizing models for cloud and edge deployment. He’s particularly focused on adapting foundation-model techniques and self-supervised learning to improve diagnostic robustness in X-ray, CT, and MRI. Based in Hunan, China, he balances technical leadership, mentorship, and system architecture oversight to drive clinically useful AI innovation.
10 years of coding experience
3 years of employment as a software developer
Master’s Degree Applied Statistics School of Mathematical Sciences, Master’s Degree Applied Statistics School of Mathematical Sciences at Capital Normal University
Contributions:4 pushes, 1 branch in 5 years 5 months
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