Andrews Sobral is an AI architect and researcher based in Paris with over two decades in software engineering and more than a decade focused on AI, ML and computer vision, combining a PhD in CV with hands-on production delivery. He designs and scales production-grade AI platforms—spanning cloud, HPC and edge—for enterprise clients, with deep expertise in MLOps/LLMOps, observability, distributed training and inference optimization. Former Head of AI at ActiveEon, he led teams to operationalize research through distributed orchestration, AutoML and model observability systems used in European research projects. A longtime contributor to open-source CV tooling (notably a C++ background-subtraction library with multi-language wrappers), he brings low-level algorithmic depth alongside systems and deployment pragmatism. He also tutors industry-focused AI practices as an adjunct lecturer and volunteers on international AI research initiatives, blending academic rigor with real-world impact. Quietly, his background spans embedded/mobile robotics to large-scale Java enterprise systems, giving him unusual breadth from devices to multi-node GPU clusters.
12 years of coding experience
14 years of employment as a software developer
Master’s Degree, Computer Vision, Image Processing, Master’s Degree, Computer Vision, Image Processing at Federal University of Bahia, Polytechnic School (UFBA)
Doctor of Philosophy (Ph.D.), Computer Vision and Pattern Recognition, Doctor of Philosophy (Ph.D.), Computer Vision and Pattern Recognition at Université de La Rochelle (L3I/MIA)
Doctoral Stage, Computer Vision and Pattern Recognition, Doctoral Stage, Computer Vision and Pattern Recognition at Universitat Autònoma de Barcelona (CVC Research Lab)
B.Sc., Mobile Robotics, Embedded Systems, B.Sc., Mobile Robotics, Embedded Systems at AREA1 Engineering School
A C++ Background Subtraction Library with wrappers for Python, MATLAB, Java and GUI on QT
Role in this project:
Back-end Developer
Contributions:17 releases, 7 reviews, 241 commits in 8 years 6 months
Contributions summary:Andrews's commits indicate contributions focused on expanding the background subtraction library, introducing new algorithms (SigmaDelta, SuBSENSE, LOBSTER, CodeBook) and fixing existing ones. This primarily involves modifying the core C++ code base, as evidenced by changes to files like `FrameProcessor.cpp` and the addition of supporting files and configurations. The user also made improvements and fixes to existing algorithms, which implies a deeper understanding of the library's functionalities.
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Andrews Sobral - Artificial Intelligence Consultant at ActiveEon