PhD student in Computer Science
Machine Learning & Language Understanding
University of Avignon - LIA

Who am I ?

I'm a young computer science enthusiast.
Always looking forward to improve state-of-the-art, and always looking to learn from the past.


Interested in computer science since my childhood, i just decided to follow the always learn and make more about computers way of life. Having the chance of being younger than the other persons around me, i always tried to use this advantage to improve my knowledge, doing personal and professional projects as much as i could.


Just graduated from the "Ingénierie du Logiciel pour la Société Numérique" Master's degree, i decided to keep up with a thesis at the University of Avignon. During these 5 years of courses, we spent a lot of time learning computer and science basics, such as algorithmics, programming, optimization and other methods. We also dealed with project, process, and team management. This master was about software engineering, i have thus a strong background in programming through multiple languages (C++, JAVA, CUDA, Python, PHP, HTML, JS, C# ... ). In order to go further you can take a closer look at the full university program

A word about the thesis

Machine Learning (ML) techniques have allowed a great performance improvement of different challenging tasks (Spoken Language Understanding, Image Processing, Motion Management, Robotic ...). Among these methods, Neural Networks (NN), recently received a great interest from researchers due to their representation capability of complex internal structures in a low dimensional subspace. However, NNs employ document representations based on a basic level (because of their 1-Dimensionality). Therefore, these basic representations reveal little in way of document statistical structure by only considering each feature as a single entity, ignoring relations between them. My thesis propose to remedy this weakness by extending the hyper-complex numbers, also called quaternions, to neural networks called QNNs for Quaternion Neural Networks. Indeed, in a real-valued neural network, multidimensional features require to be reduced to a one dimensional vector before the learning process, while an appropriate solution is to process a multidimensional input as a single homogeneous entity. All these drawbacks can be alleviated thanks to the fourth dimensionality of quaternions and the hamilton product.

This thesis first proposes an integration of quaternions to state-of-the-art models such as : deep, recurrents, convolutionals, and adversarials neural networks. This integration rely on adapted and well-suited algorithms to fit the quaternion algebra specificities, and on a GPU implementation of quaternion neural networks. Then, a new type of neural network expressly designed for hyper-complex numbers wil be investigated, including a specific learning process and a well-adapted structure. This method has already reached promissing results that will be reported on my ResearchGate homepage and below.

Feel free to contact me if you want furthermore informations !


Awards and grants

International conferences

National conferences


ORKIS - PhD Fellowship

Orkis is a a french company based on Aix-en-provence, France. They are specialised in assets and data managements with well-known customers such as L'Oréal, Dassault, or the governement of France. The collaboration between the LIA (and thus the University of Avignon) started with a previous PhD fellowship which has now ended. In order to enhance their tools, they decided to pursue this collaboration with a new PhD student, me. My job involves many taks, from automatic indexation on speach recognition to image processing and machine learning. For more informations about the company, feel free to visit the Orkis website.


All the tutorials and practical work classes are dispensed in addition to my standard research job

Year 2016/2017

TeachingTutorialsPractical WorkTotal
Advanced programming and projects (B.Sc.)12h18h30h
Agorithms and programming (B.Sc.)12h18h30h

Year 2015/2016

TeachingTutorialsPractical WorkTotal
C2I Certification (B.Sc.)60h

Year 2013/2014

TeachingTutorialsPractical WorkTotal
C2I Certification (B.Sc.)60h


Lab address

339 Chemin des Meinajariès
84911 Avignon, France

Mail & Phone
+33 490 843 577