À propos de Issa
I am a Deep Learning Engineer with 5 years of experience in computer vision related problems.
I worked with big companies and startups, in R&D and production. Throughout my experience, I acquired a strong knowledge in machine learning/deep learning.
In addition, I was responsible of maintaining the code and appling best practices, in order to serve a clean and flexible architectures.
A brief examples of what I did in my past jobs:
- Worked on a variety of vision problems (document understanding, image segmentation, depth estimation, visual inspection).
- Implement advanced pipelines with TensorFlow & PyTorch.
- Design and optimize deep learning networks for limited resources environment.
- Develop data collection and visualization tools (Selenium, Dash).
- Debug and improve complex architectures and propose new solutions (vision-language models, UNet etc...).
- Refactor and maintain complex code using coding best practices.
After all, I am a problem solver and I am ready to help you benefit from the power of deep learning.
Arabe
Bilingue ou natif
Français
Bilingue ou natif
Anglais
Capacité professionnelle complète
Accepte de travailler sur site
Paris (jusqu’à 50 km)
Expériences
- RYTE FranceComputer Vision EngineerSECTEUR MÉDICALjanvier 2024 - Aujourd'hui (2 ans et 5 mois)Paris, FranceI am working on Visual Document Understanding.Tasks:
- Perform SOTA analysis on different visual document understanding techniques (w/ and w/o OCR).
- Develop a Python scrapper to collect data.
- Develop a web app for visualizing and curating the data.
- Finetune and evaluate an end-to-end large language and vision model for information extraction.
Technologies: Python, Dash, PyTorch, Hugging Face, Swin Transformer, BART. - 7 Sensing SoftwareComputer Vision EngineerHIGH TECHfévrier 2022 - janvier 2024 (1 an et 10 mois)Paris, FranceI worked on 2 different projects: monocular depth estimation and visual inspections.1. Monocular depth estimation from RGB and dToF sensor:
- Design and optimize deep learning models for limited resources environment .
- Port and benchmark the trained models on mobile phone.
- Apply a statistical analysis study to reduce the gap between real and synthetic data.
- Refactor and apply development best practices (code architecture, design patterns).
2. Visual Inspection- Design and benchmark deep learning solutions for anomaly detection, classification and segmentation.
- Research and implement unsupervised method for labelling assistance.
- Pretrain networks using self-supervised learning techniques (MoCo, SimCLR).
In addition, I proposed, recruited and supervised an intern to work on reducing temporal inconsistency in video depth estimation. - Self EmployedDeep Learning InstructorEDUCATION & E-LEARNINGfévrier 2023 - Aujourd'hui (3 ans et 4 mois)I created my online course, called Intuitive Deep Learning, where I explain the foundations of Deep Learning in an intuitive and connected way.Tasks:
- Create 10 lessons, 2 hands-on, multiple choice questions covering the foundation of Deep Learning, based on books, papers and my own experience.
- Create animations using Python for an intuitive explanation of complex concepts.
- Design the website landing page, and improve the content format with CSS.
- Prepare the marketing content (logo, videos, animations, posts etc...).
Here is the website: https://intuitive-dl.thinkific.com/courses/intuitive-dl
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Formations
- Master of Science in EngineeringTelecom ParisTech2019Master of Engineering (MEng), Data Science
- Master of EngineeringLebanese University - Faculty of Engineering III2019Master of Engineering (MEng), Electrical and Electronics Department