Carson Mcneil is a computational neuroscientist and machine vision expert with 13 years of experience applying deep learning and statistical methods to large-scale imaging problems across industry and academia. After early engineering roles at Google, he pursued neuroscience research at UC Berkeley’s Gallant Lab where he adapted modern vision models to human fMRI and primate electrophysiology, then transitioned to Verily to lead machine vision efforts in autofluorescence and virtual staining of massive microscopy datasets. He combines hands-on ML research, production software engineering, and data engineering to deliver validated generative models and patented solutions for medical imaging. Based in San Francisco, he now contributes at founding technical staff level to multidisciplinary neurotech work, blending experimental design with scalable ML pipelines—an uncommon mix that bridges lab neuroscience and production-grade imaging systems.
13 years of coding experience
13 years of employment as a software developer
Master's degree Neuroscience, Master's degree Neuroscience at University of California, Berkeley
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