Summary
Gal Mishne is an associate professor at UC San Diego's Halıcıoğlu Data Science Institute specializing in geometric representation learning, manifold learning, spectral graph theory, graph signal processing, and computational neuroscience. With a PhD in Electrical Engineering from Technion and nine years of academic experience spanning Yale and UCSD, he blends deep theoretical insight with applied image- and signal-processing expertise that began in industry defense projects. His work connects spectral methods and geometry to neural data and graph-based learning, often revealing structure that standard ML pipelines miss. Known for coordinating interdisciplinary forums early in his career, he brings a collaborative, systems-oriented approach to advancing both theory and practical tools in data science.
9 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Technion - Israel Institute of Technology
English, Hebrew