Luzhou Zhang is a quantitative analyst with 9 years of engineering and research experience, blending neuroscience training from Johns Hopkins with strong software engineering skills. Currently at TEAM EDEFI and as a researcher in JHU's Psychological and Brain Sciences department, he develops quantitative methods at the intersection of AI and brain science. His background includes building neural networks for petabyte-scale cortical connectomics at JHU APL and engineering integrations for fiber-optic gyroscope validation, reflecting both large-scale ML and practical systems experience. Known on GitHub for QDK software engineering work, he brings a pragmatic, research-informed approach to deploying AI-powered segmentation and quantitative analytics.
Contributions:29 commits, 1 PR, 28 pushes in 1 year 9 months
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