Georgios Karnas is a Member of Technical Staff with a decade of experience building high-performance web and visualization tooling, currently shaping visual systems at OpenAI from Palo Alto. He blends front-end craftsmanship with full-stack systems work, having led UI efforts at Uber (including authoring the open-source nebula.gl) and contributed core features and shader work across vis.gl projects like luma.gl and deck.gl. His background spans product-critical internal platforms at Snap to growth-focused engineering at Facebook, showing comfort across scale, real-time graphics, and content moderation tooling. A Cambridge MPhil graduate, he pairs rigorous academic training with pragmatic engineering — notable for fixing tricky glTF/GLB parsing and advancing PBR and scenegraph capabilities in visualization stacks.
10 years of coding experience
5 years of employment as a software developer
Master of Philosophy (MPhil) Computer Science, Master of Philosophy (MPhil) Computer Science at University of Cambridge
Bachelor of Science (BSc) Computer Science, Bachelor of Science (BSc) Computer Science at University of Piraeus
A suite of 3D-enabled data editing overlays, suitable for deck.gl
Role in this project:
Front-end Developer
Contributions:161 commits, 134 PRs, 278 pushes in 2 years
Contributions summary:Georgios primarily contributed to the development and maintenance of the user interface components within the `nebula.gl` project, which is a suite of 3D-enabled data editing overlays for deck.gl. The commits show the creation and modification of React components, as well as the integration of examples, and the addition of features such as a GeoJSON editor. The changes include improvements to styling, and the addition of new components and functions.
Contributions:33 commits, 35 PRs, 39 pushes in 1 year 1 month
Contributions summary:Georgios primarily contributed to the `loaders.gl` project by fixing issues related to glTF and GLB parsing and loading. They addressed bugs in buffer handling, image loading, and texture loading within the glTF parser. The user also implemented features like asynchronous image loading and support for the KHR_techniques_webgl glTF extension. Additionally, the user made several code improvements, including addressing eslint issues and optimizing the codebase.
csvloadersbasisdracobig-data-visualization
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