Postdoctoral Fellow at Columbia's Mortimer B. Zuckerman Mind Brain and Behavior Institute
Berkeley, California, United States
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Summary
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Logan Thomas is a software engineer and postdoctoral fellow with 11 years of experience blending signal processing, machine learning, and applied mathematics on large-scale scientific imaging problems. Based in Berkeley, he has built production-grade C++ audio tools and patent-pending parallel audio processing algorithms, then shifted to high-throughput electron microscopy software and ML-driven image segmentation at Harvard and Columbia-level research institutes. His work spans instrument control, massive data pipelines, and quantitative analysis—applying spectral graph methods and custom analytics to neural connectivity and EM datasets. Trained with a PhD in Biophysics from UC Berkeley and dual undergraduate majors in mathematics and physics, he pairs rigorous theoretical grounding with pragmatic software engineering. Colleagues rely on him to bridge experimental hardware, scalable software, and advanced analytics to turn raw imaging into actionable scientific insight. A less obvious strength is his long-running habit of translating deep mathematical ideas into robust, production-ready code across domains.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Biophysics, Doctor of Philosophy - PhD Biophysics at University of California, Berkeley
Mathematics/Physics Double Major Mathematics, Mathematics/Physics Double Major Mathematics at Northeastern University
Mathematics/Physics Double Major, Mathematics/Physics Double Major at University of Massachusetts Dartmouth
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Logan Thomas - Postdoctoral Fellow at Columbia's Mortimer B. Zuckerman Mind Brain and Behavior Institute