A De Souza
AI Content Strategist
Tainan Metropolitan Area Taiwan
Summary
👤
Senior🎓
Top SchoolA De Souza is an AI content strategist and game solutions architect with 11 years of experience building narrative-driven, physics-aware agents and production-ready game AI. Based in Tainan, Taiwan, he blends deep technical chops—C/C++, Unity/C#, cross-platform compatibility and build-system expertise demonstrated by contributions to the widely used Caffe deep-learning repo—with creative instincts from a background in architecture and classic literature. He rethinks behavior trees (reformulating them as three-state logic) to deliver responsive, efficient real-time AI and has shipped commercial titles and engines as an indie lead and senior engineer. As an entrepreneur and mentor he pairs hands-on engineering with product sensibility, bootstrapping story-centric platforms and guiding teams on combat and control systems. This mix of research, production, and cross-disciplinary training gives him a rare ability to turn narrative goals into robust, maintainable agent systems.
11 years of coding experience
15 years of employment as a software developer
Classic Literature, Classic Literature at Sorbonne UniversitéBSc Multimedia Technology, BSc Multimedia Technology at Brunel University of LondonPhD Computing, PhD Computing at Goldsmiths, University of LondonDEFA (B. Des. equiv.) Architecture, DEFA (B. Des. equiv.) Architecture at Ecole d'Architecture de Paris-Val-de-Seine
English, French, Chinese
Github Skills (18)
dependency-management10
opencv10
c-language10
leveldb10
build-system10
cmake10
deep-learning10
cprogramming-language10
build-automation8
lmdb8
machine-learning7
machine-vision7
computer-vision7
realtime4
py4
Programming languages (11)
Github contributions (5)
BVLC/caffe
Jun 2015 - Dec 2015
Caffe: a fast open framework for deep learning.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:36 commits, 23 PRs, 61 comments in 5 months
Contributions summary:A primarily contributed to the build and dependency management aspects of the Caffe project, specifically focusing on making external libraries like OpenCV, LMDB, and LevelDB optional. This involved modifying build scripts (CMake) and source code to conditionally include these dependencies. The user also addressed build system issues, such as ensuring functions returned values and replacing outdated system calls. Additionally, the user added or modified build configurations to enhance build process reliability and portability.
pytorchvisiondeep-learningmachine-learningcaffe
active-logic/howl
Aug 2020 - Feb 2021
Symbolic notation engine
Contributions:19 releases, 28 commits, 4 PRs in 5 months
symbolicnotation
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