Eran Geva is an independent algorithm specialist with 11 years of experience building high-performance computer vision, 3D generative modeling and GPU-accelerated solutions for products ranging from AR/VR prototypes to embedded automotive maps. He combines deep C++/CUDA expertise with practical use of OpenCV, TensorFlow, Unity/Unreal and Three.js, and has a track record of shipping mesh, voxel and toolpath algorithms at companies like Autodesk and TomTom. As a consultant he tackles diverse problems — GIS, robotics vision, 3D projection and unwrapping — and has also delivered community-facing projects such as a web radio and a 3D mobile game. Eran contributes to prominent open-source work in three.js, improving geometry loading and memory use, reflecting a focus on pragmatic, performance-minded refactors. His academic background in bioinformatics and an MSc in computer science underpin a strong foundation in algorithms and GPU-accelerated research.
11 years of coding experience
17 years of employment as a software developer
Computer Programming, Computer Programming at Software School
BSc, Bioinformatics, BSc, Bioinformatics at Ben-Gurion University of the Negev
Contributions:5 reviews, 11 commits, 12 PRs in 4 years 2 months
Contributions summary:Eran primarily contributed to the `three.js` library, focusing on improving the geometry and loading functionalities. They refactored code within `STLLoader.js` to improve STL file classification and parsing, demonstrating a good understanding of file format handling. Furthermore, they optimized the geometry creation process in `Geometry.js` by avoiding unnecessary memory allocations and improving the readability of existing code.
Doubly-Connected-Edge-List (DCEL) implementation for three.js
Contributions:47 commits, 2 PRs, 42 pushes in 8 days
3ddcelhalfedgejavascriptthreejs
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Eran Geva - Independent Algorithm Specialist at eran.dev