Description

After having made expertise in the field of computer vision, video analysis, deep learning, and mechanical engineering within Paris Saclay. I want to build my skills on this by applying all my technical knowledge and by exchanging it with professionals.

Langues

Français
Capacité professionnelle limitée
Anglais
Capacité professionnelle complète
Persan
Bilingue ou natif

Préférences en matière de lieu de travail

Accepte de travailler sur site

Toulouse (jusqu’à 50 km), Paris (jusqu’à 10 km), Lyon (jusqu’à 20 km)

OMIA
computer vision and deep learning engineer
février 2022 - Aujourd'hui (4 ans et 3 mois)
Angoulême, France
Development of a RAG platform, integrating the ChatGPT API for
business document analysis:
Development of a real-time question-answering solution for large
business documents using RAG and ChatGPT API.
Prompt engineering to refine interactions with GPT models.
Using React for the frontend and FastAPI for the backend, with a
scalable and high-performance architecture, hosted on GCP.
Continuous technological monitoring to integrate the latest
advances in AI and NLP and apply them to professional projects.
Collaboration with both technical and non-technical teams to
facilitate AI solution adoption through workshops and
educational sessions.
Developed a complete end-to-end solution for car damage
detection, including building three models: Plate Detection, Damage
Detection, and Car Parts Detection (segmentation).
Trained and optimized AI models using CUDA, TensorRT, and ONNX,
deploying them on cloud platforms like GCP and Scaleway.
Built the entire web application using Django, HTML, JavaScript,
Docker, and SQL/PostgreSQL to provide a seamless interface for car
damage detection.
Handled every stage of the project, from model development and
optimization to the full-stack implementation of the web app.
Python Pytorch CUDA OpenCV Google cloud
Projet EUGENE, ISAE-Supméca,
Chercheur Doctorant
CENTRES DE RECHERCHE
février 2018 - septembre 2021 (3 ans et 7 mois)
93400 Saint-Ouen, France
- Object detection with RCNN and YOLO to detect the perfume bottle.
- Develop a Graphical User Interface (GUI) with Python and MATLAB to automatically reduce the movement of liquid inside the moving container.
- Develop an image processing algorithm to detect the movement of liquid in different shapes of containers.
- Sloshing (liquid movement) in perfume bottles was reduced by 45% using real-time video analysis and a genetic algorithm.
- Sloshing simulation inside the container by presenting a mathematical formulation of fluid dynamics.
- Development of an image processing algorithm with Python and MATLAB to detect in real time the movement of liquid in different shapes of containers.
Python Matlab OpenCV Pytorch
INSA
Stage Ingénieur
AÉRONAUTIQUE & AÉROSPATIALE
mars 2017 - septembre 2017 (6 mois)
United States
- Forecast the best forecasting method for business aircraft spare parts demand.
- Running five different classifier prediction methods.

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Doctorat Sciences Mécaniques
Université Paris Saclay,
2021
Doctorat Sciences Mécaniques
Master 2 en Ingénierie Mécanique
Arts et Métiers ParisTech,
2017
Master 2 en Ingénierie Mécanique