Summary
Andrew Zaharia is a Director of Data Science and computational neuroscientist with 11 years of experience applying machine learning, neural modeling, and electrophysiology to understand visual intelligence in both brains and artificial networks. He designs and implements novel visualization and dimensionality-reduction methods that reveal how neural networks and visual brain areas decode objects, and has translated that research into production analytics and dashboards for policy organizations. Equally comfortable in Python/PyTorch and MATLAB, he combines high-performance cluster computing with rigorous statistical modeling and experimental design to tackle adversarial robustness, hyperspherical inference, and biologically inspired architectures. Based in New York, he has led and mentored teams across academia and nonprofits, shipping open tools and prototypes that bridge basic science and real-world decision-making. An understated strength is his ability to boost experimental throughput dramatically (e.g., 121x in prior work), turning principled theory into scalable, reproducible systems.
11 years of coding experience
16 years of employment as a software developer
PhD Computational Neuroscience, PhD Computational Neuroscience at New York University
Master of Arts (MA) Cognitive & Neural Systems, Master of Arts (MA) Cognitive & Neural Systems at Boston University