Deep Learning researcher at AZmed, I am fascinated by AI, Deep Learning and Computer Vision. I truly believe in the #AIforGood movement, that aims to place the AI at the service of the human and the common good. In the years to come, I aspire to join major projects in e-health, that will revolutionize the current practices.
A powerful detection algorithm for one medical center, but unsuitable for another. This is one of the major problems faced by research teams wishing to deploy their models on a large scale. In this article, I introduce this challenge called Domain Adaptation in the context of medical imaging, based on my experience at AZmed.
Research report comparing two main approaches - Radiomics and Deep Learning - to detect malignant soft tissue tumors directly on magnetic resonance imaging.
Utilities to download (CLI) and load an MRI brain tumor dataset with Python, providing 2D slices, tumor masks and tumor classes.
Application of object detection / segmentation (MaskRCNN and RetinaNet) on Mars satellite images. The goal was to detect automatically craters.
Implementation of the reinforcement learning technique Q-Learning. The environment was MountainCar (OpenAI Gym), where the goal is to teach a car to swing from left to right so that it can climb the mountain.
Development of various visualizations to respond to the VAST mini-challenge 1 of 2018. The goal was to discover if the actions of a company had led to the migration of birds. Spatio-temporal data analysis led to the development of an interactive map to observe the movements of different species. Spectral analysis of bird songs has also revealed interesting facts.
Maximum a posteriori (MAP) estimation on NMF (non-negative matrix factorization), applied on faces.
Development of an Open Source archiving system allowing the storage of any type of data. The users can interact with web-based system through the website or directly from scripts (using the developed Python library). Originally, the application was designed and developed within SoftBank Robotics to store tests performed on NAO and Pepper robots.
Participation in two editions of the French Robotics Cup with DaVinciBot, association of the Pôle Universitaire Léonard de Vinci.
A web application that makes it easy to find all Michelin starred restaurants that currently offer promotions in France.
Web application to easily explore a MongoDB database, containing the 5000 best selling movies on Amazon.
The goal of this project was to develop an Android application similar to Youtube, using their API.
Classes followed during the 1st semester:
Classes followed during the 2nd semester:
Major: Computer Science, Big Data and connected objects
Activities and associations : Member and Communication manager of the association of robotics DaVinciBot.
Example of the classes followed:
Major: Computer Science
Thanks to an exchange program, I had the opportunity to study in this american university for one semester.
Article about my experience (by ESILV)
Classes followed:
GPA: 4.0 (A)
Scientific Baccalaureat, with high honours
FishFriender is an online platform that aims to modernize the angling industry.
➢ Mission: automate data recovery and process partner data to adapt and insert them into the application database.
The partner data were either in Excel sheets or in web pages. I extracted the data using web scraping techniques.
✹ Tech used: Node.js, JavaScript, SQL, JSON.
✹ Environment: Mac OS
DaVinciBot is an association of Leonard De Vinci University, which aims to gather all the students interested in robotics. It was first created to participate to the French Cup of Robotics. Now we work on several projects like InMoov, a life size humanoid robot we are printing in 3D.
Summer Job in a sports shop.
Summer Job in an amusement park.
- Python # Numpy, Pandas, Scikit-Learn, TensorFlow, Keras, Matplotlib
- Web development # HTML, CSS, JavaScript, jQuery, Node.js, Express.js
- Databases # SQL (MySQL, PostgreSQL), NoSQL (MongoDB), ElasticStack
- C# / Java
- R
- Git
- Jupyter
- LaTeX
- Unix
- RStudio
- VS Code
- Android Studio
- Adobe Photoshop
- 🇫🇷 French # native
- 🇬🇧 English # fluent
- 🇪🇸 Spanish # notions
