Casey Meisenzahl is a software engineer and PhD candidate with 11 years of experience building practical ML and engineering systems across industry and research. At RIT they developed state-of-the-art medical ML methods—like MeiBRD for 3D liver registration and BOATMAP for ECG-based localization—demonstrating strong skills in PyTorch, Bayesian optimization, and GPU-scale training. Previously at Snap they improved CI and observability using Go, SQL, Grafana, and automation tooling, and earlier internships sharpened cross-team delivery and automation skills. Casey combines hands-on production engineering with rigorous research, translating clinical signal-processing problems into deployable, interpretable solutions, and has mentored junior researchers to bridge theory and practice.
11 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computing and Information Science, Doctor of Philosophy - PhD, Computing and Information Science at Rochester Institute of Technology
Associate's degree, Computer Science, Associate's degree, Computer Science at Monroe Community College
Spatially joins two line features within a radius and selects the feature with the most similar polar angle
Contributions:36 commits, 2 PRs, 18 pushes in 1 year 1 month
joinsradiussimilarsplinesangle
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