- MVA (Mathematics, Computer Vision, Machine Learning) is one of the best master’s program in applied mathematics that focuses on the theoretical foundations of machine learning as well as on modern developments in the field.
- Relevant coursework: Convex optimization, Large scale convex optimization, Numerical imaging, Image Denoising, Point clouds and 3D modeling, Deep Learning in practice, Kernel methods, Deep reinforcement learning, Random matrix theory, Medical imaging.
- Engineering degree in applied mathematics and datascience.
- Relevant coursework: Probability, Stochastic processes, Statistics, Optimization, Advanced machine learning, NLP, Computer vision, ML in network science
- Exchange semester at NUS.
- Relevant coursework: Economy, Stochastic processes, Statistics for acturial science, Decision making methods
- Two-year intensive preparation in Maths and Physics for the highly competitive entrance exams to the French engineering Grandes Ecoles.
- Awarded the Tunisian government excellence fellowship (top 0.1% national wide)
- Worked in the corporate research team on controlled generation of visual content using deep learning
- Used generative models (e.g., GANs) for image synthesis and image editing
- I tackled the subjects of GAN training with internal data, control mechanisms definition for content generation, GAN image inversion, real image editing and image similarity
- Proposed, implemented and tested meaningful improvements over the state of the art methods
- Worked on a predictive maintenance project for a European industrial leader
- Designed and developed Computer Vision solutions to detect anomalies in electrical installations (pylons, high voltage lines) from aerial shots made up of videos of different types (HD, thermal, ..)
- Implemented and adapted state of the art methods for object detection, object tracking and anomaly detection
- set up an automatic data annotation process