Created a new synthetic data generation channel using python to serve as Rendered.AI's factory example channel.
• Utilized various Python geospatial libraries and optimized system calls to a prominent geospatial pre-rendering API to help transition one of Rendered.AI's flagship channels to a more efficient tiled system.
• Helped review and test production level code used at various computer vision and pattern recognition conferences while also adding relevant documentation to allow customers to create synthetic datasets across various domains.
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SSDA Lab at University of Washington
Undergraduate research Assistant
Seattle, WA, United States, 98194
September 2021 - present
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Paul G. Allen School of Computer Science and Engineering