Johan Azambou
Software Developer | Computational Geometry + AI Research | Java, Python, C++ | 3D Graphics + Machine Learning | MSc. Computation & Applied Mathematics @ UW, Seattle | Open to New Grad/Entry Level Opportunities (2025)
- Role
- Research Fellow-computer Vison & Scientific Computing at Mit Computer Science And Artificial Intelligence Laboratory Csail
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Johan Azambou
I\'m a passionate software developer and researcher with a strong background in applied mathematics, computer science, and human-centered technology. I specialize in building scalable backend systems, applying machine learning to 3D graphics, and solving complex scientific problems through numerical methods. My experience spans- Research at MIT CSAIL on geometric deep learning for 3D object recognition and mesh reconstruction- Software development at Trimble SketchUp, building tools for AI-generated 3D model editing using C++- NLP and voice tech at SayKid, where I built interactive voice games deployed on Alexa, reaching 2500+ users- Computational math research, achieving 16-digit precision in simulations of fluid flow and rational approximations. I’ve also led full-stack projects (JavaScript, Node.js), developed AR/VR experiences, and trained deep learning models for sentiment analysis. Recently completed my MS. in Computational & Applied Mathematics at the University of Washington, and seeking opportunities in software engineering, AI/ML, or applied research for Summer/Fall 2025. Let’s connect!
Experience
Research Fellow-computer Vison & Scientific Computing
Mit Computer Science And Artificial Intelligence Laboratory Csail
May 2024 — Present
Applied spatial analysis and geometric deep learning to improve 3D object recognition and real-time mesh reconstruction for computer vision applications • Developed AI-driven solutions for solving complex PDEs on non-trivial geometries, accelerating simulation pipelines and enabling more accurate scientific visualization • Achieved zero-loss fidelity in animated 3D mesh reconstruction using signed distance functions, improving realism and efficiency for VR/AR use cases • Contributed to open-source research in computational geometry and deep learning frameworks for physical simulation
Education
University of Washington
Master of Science - MS
2024 — 2025
Macalester College
Bachelor of Arts - BA
2020 — 2024
Bilingual Grammar School
Academic
2011 — 2018
CodePath
Certificate In Intermediate Software Engineering
2023 — 2023
Misongi College Access Program
Certificat de formation générale (CFG)
2018 — 2019
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