Geoffrey Pruvost
Directeur Technique (CTO) at Diag n'Grow
Lille, Hauts-de-France
Summary
👤
Senior🎓
Top SchoolGeoffrey Pruvost is a CTO and former PhD in computer science with 11 years of experience building AI-driven, full-stack platforms—currently leading technical strategy at Diag n’Grow, which values and prices intangible assets like patents and software. He blends research-grade expertise in optimization and machine learning with hands-on engineering across VueJS, Django, PostgreSQL and LLM toolchains (Mistral, Azure OpenAI, Langchain), shipping production-grade features and data pipelines on cloud providers such as Clever Cloud and OVH. Previously co-founder and CTO of Optimo Technologies, he turned transport prediction research into a deployed mobility assistant backed by Inria, demonstrating an ability to commercialize academic R&D. He also teaches practical AI agent development and maintains a consultancy background, bringing a rare mix of academic rigor, product delivery, and IP-focused financial analytics to technology leadership.
11 years of coding experience
6 years of employment as a software developer
Thèse de doctorat Informatique, Thèse de doctorat Informatique at University of Lille 1 Sciences and TechnologyMaster I2L Informatique, Master I2L Informatique at Université du Littoral Côte d'OpaleBaccalauréat Série scientifique, Baccalauréat Série scientifique at Lycée Giraux Sannier
French, English
Stackoverflow
653reputation
116kreached
5answers
2questions
Github Skills (126)
multi-objective-optimization10
automation10
optimization-methods10
nodejs10
pypi10
rapidapi10
operations-research9
api9
home-automation9
grpc9
react-native-module9
python9
ruby9
native-module9
home-assistant9
Programming languages (10)
Github contributions (5)
geoffreyp/geoffreyp.github.io
Aug 2018 - Mar 2024
Personal website
Contributions:4 PRs, 90 pushes, 1 branch in 5 years 8 months
reactnextjs
moead-framework/framework
Nov 2019 - Oct 2022
MOEA/D is a general-purpose algorithm framework. It decomposes a multi-objective optimization problem into a number of single-objective optimization sub-problems and then uses a search heuristic to optimize these sub-problems simultaneously and cooperatively.
Contributions:10 releases, 24 reviews, 269 commits in 2 years 11 months
modular-frameworkheuristicoptimization-methodspythonpypi
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