Ash Hoover
AI R&D Lead at Planet
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolAsh Hoover is an AI R&D lead with 12 years of experience applying advanced machine learning and geospatial systems to turn satellite imagery into operational insights. At Planet they bridge research and product, pioneering multimodal embeddings, vision-language models, and foundation-model prototypes that scale across environmental monitoring, disaster response, and commercial analytics. Their background spans physical chemistry research, molecular spectroscopy, and production ML infrastructure, enabling a rare combination of scientific rigor and engineering pragmatism. Ash has led platform integrations around open geospatial standards (STAC, COG, WMTS) and contributed practical notebooks and demos that make Planet’s APIs and raster products more accessible to developers. Known for stepping into interim leadership roles during transitions, they excel at aligning cross-functional teams, partnerships (including work with Anthropic, NVIDIA, and Google), and technical strategy to drive impact at planetary scale.
12 years of coding experience
13 years of employment as a software developer
M.S. PhD - ABD Physical Chemistry, M.S. PhD - ABD Physical Chemistry at University of California, BerkeleyAdvanced Software Engineering Immersive, Advanced Software Engineering Immersive at Hack ReactorBachelor's Degree Chemistry and French, Bachelor's Degree Chemistry and French at William & Mary
English, French
Github Skills (11)
data-visualizations10
jupyter-notebook10
data-visualization10
data-visualisation10
sens10
python10
data-analysis10
pandas9
api9
apim8
api-design8
Programming languages (5)
Github contributions (5)
planetlabs/notebooks
Oct 2019 - May 2022
interactive notebooks from Planet Engineering
Role in this project:
Data Scientist
Data ScientistContributions:24 reviews, 24 commits, 19 PRs in 2 years 7 months
Contributions summary:Ash contributed to several Jupyter notebooks focused on analyzing Planet Analytics API data. Their work involved fixing base URL links, updating Python versions, and providing examples of fetching results from subscriptions. They also created notebooks for visualizing raster results and webtiles imagery, and added a building summary statistics demo. These contributions suggest a focus on data processing, visualization, and API interaction within the context of remote sensing data.
apidata-analysispythonsatellite-imageryplanet
Synesthesia-2/Synesthesia
May 2014 - Jul 2014
Contributions:147 commits in 2 months
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