Engineering

Lilly Thomas

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Lilly is a machine learning engineer at Development Seed. She has expertise in applying deep learning techniques for land cover classification and feature extraction from satellite, aerial and UAV imagery. Her primary interests lie in coupling machine learning with the natural sciences, particularly oceanography.

Prior to joining Development Seed, Lilly worked as a Data Scientist at OmniEarth, followed by EagleView Technologies. In both roles, she worked with heterogeneous data formats and built models that were deployed and scaled in cloud-based pipelines. Outside of work, Lilly has dedicated time modeling coastal terrain morphology and detecting rip currents in multispectral satellite imagery with sediment-specific band ratios.

Based in LA, you can find Lilly surfing, hiking or practicing yoga - she is a certified yoga teacher - outside of work. Lilly received a B.A. from UCLA.

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