I recently graduated from IMT Mines Ales as an Artificial Intelligence Engineer. I'm passionate about working with data and developing tools that are linked to machine learning. I also enjoy designing data-driven visualizations and user experiences on the web.
Implementing a syntax highlighting system only using neural networks.
Simplest ML problem solved with TFJS, a home-made dataset and visualized with D3.
Visualizing the differences between the identification of autonomous and time-dependent dynamics in COVID trajectories.
Plotting the difference in fitting data with the SINDy algorithm with rational basis functions.
Using system-identification algorithms to explore the dynamics in COVID-related data.
A study of the obfuscation/minification usage in the open-source Android developement apps. A crowd-sourcing technique based on ML is proposed to help developers write more effective obfuscation and minification rules.
Uncertain modeling of low-quality data from non-reproducible experiments. The goal is to allow uncertain hypothesis testing for unreliable data. The proposed techniques are applied to real-world clinical data of a comparison of two mattresses.
Report about my final internship at the chair of Applied Analysis at the Friedrich Alexander University in Erlangen under the supervision of Prof. Enrique Zuazua. We used system identification techniques in order to study the dynamics of COVID-related data.