Kamenan N'gadi is a PhD student and data scientist with 10 years of hands-on experience applying machine learning, applied mathematics, and software engineering to real-world scientific and agricultural problems. He designs end-to-end image processing and uncertainty quantification pipelines for bioindication and biomedical imaging, and has built AI tools to support breeding decision-making and GWAS interpretability. Equally comfortable in research and production, he contributes to game-engine and FiveM roleplay open-source projects—working on core Lua client/server features and low-level file-format support—illustrating a wide technical range from interactive systems to scientific ML. His background includes improving NIRS calibration with machine learning, spatial yield modeling, and synthetic-data generation for robust model training. Based in Massy, Île-de-France, he combines rigorous academic training with practical engineering, often reducing labeling needs via weakly supervised and interactive learning strategies.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Mathématiques et informatique -IA, Doctor of Philosophy - PhD, Mathématiques et informatique -IA at CentraleSupélec
CS-IODAA, Intelligence artificielle, CS-IODAA, Intelligence artificielle at AgroParisTech
mathématiques appliquées al'industrie, l'ingenieurie et l'innovation, Mathématiques appliquées, mathématiques appliquées al'industrie, l'ingenieurie et l'innovation, Mathématiques appliquées at Université Paul Sabatier Toulouse III
Contributions summary:Kamenan primarily contributed to the client-side code of an ESX-based police job system within the FXServer environment. They modified the client-side Lua files extensively, adding new features and updating existing ones. The user also updated SQL files, suggesting backend database modifications. Furthermore, they integrated phone number functionality into the police job system.
Contributions summary:Kamenan primarily added client-side and server-side Lua files related to a FiveM roleplay framework. The contributions include implementing features for instance management within the game, such as creating, entering, and leaving instances. They also worked on integrating with other components like the property and garage systems, indicating a focus on the overall game mechanics and backend logic.
luafivemesx-frameworkesx-legacygrandtheftauto5
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