Connor Lane

Connor Lane is a skilled Scientific Software Developer at the Child Mind Institute, where responsibilities include employing data science, machine learning, and computer vision techniques to extract insights from large-scale brain imaging data. Prior experience includes working as a Computer Vision Scientist at MITRE, where Connor Lane developed robust algorithms to efficiently learn from limited data, and as a Research Assistant at The Johns Hopkins University, where methods for analyzing high-dimensional data were created and assessed. Earlier roles included serving as a Research Program Coordinator at The Johns Hopkins University, focusing on the effects of experience on brain function in blindness while developing tools for MRI data analysis. Connor Lane holds a Master of Science in Computer Science from The Johns Hopkins University and a Bachelor of Science in Mathematics and Philosophy from UCLA.