I'm Mohamed Maouche, I am currently working on private machine learning for speech processing at Inria in the Magnet Team (MAchine learninG in information NETworks). I have receivied a PhD in computer science from INSA-Lyon France in 2019 (working on location privacy).
My main interest is to build machine learning systems that manages a good trade-off between privacy and utility. I explore anonymization techniques and re-identification threats on different data types and application structures.
Working on private machine learning for speech processing along side Aurélien Bellet, Marc Tommasi and Emmanuel Vincent.
Teaches computer science in the computer science department of INSA-Lyon (Dept. IF) and in the first cycle department (Dept PC).
In the field of Optimization in Operations research. Working on the Vehicle Routing Problem (VRP) and the Robust VRP with Time windows constraints.
Study of a formal method designed by a research team in the University of Queensland (Australia) which purpose was to transform a BPMN model into a Petri network.
This toolkit encapsulates multiple python implementations of anonymization metrics from the state of the art.
A re-identification attack based on learning from multiple past behaviours to re-identify short mobility traces.
Location Privacy Protection Mechanism HMC (Heat Map Confusion). To protect mobility trace against re-identification attack using heat map profile transformation while maintaining utility.
Experiment on re-identification attack on mobility data (AP-Attack, POI-Attack...).
Python (scikit-learn, scipy), Java, Scala, C/C++
HTML, JavaScript, XML, XSL, XPath, XQuery...
Linux, MySQL, MongoDB, IOS (cisco)
