About 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.
Arabic
Native or bilingual
French
Native or bilingual
English
Fluent
Can work on-site
Paris (up to 50km)
Experience
- RYTE FranceComputer Vision EngineerMEDICALJanuary 2024 - Today (2 years and 5 months)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 EngineerTECHFebruary 2022 - January 2024 (1 year and 10 months)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 AND E-LEARNINGFebruary 2023 - Today (3 years and 4 months)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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Education
- 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