- Currently working as a Machine Learning Scientist at iAudiogram (My Medical Assistant SAS)
- Previously released the book: "Essential Math for Data Science"
- Previously working as a Machine Learning Scientist at Ava Accessibility .
- Previously Ph.D student at the École Normale Supérieure
Data Science
- Machine Learning / Deep Learning (Sklearn, Keras)
- Data processing (Pandas, Numpy)
I am currently managing a project for bird detection using deep learning with the non profit organization Wazo in Paris. This project has been selected in the season 06 of DataForGood Paris from September to December 2019.
I am also bloging here on mathematics for machine learning and deep learning. I think that computer science is a great way to learn theoretical knowledge with a practical approach.
At Ava, I worked on creating and maintaining machine learning pipelines for speaker diarization from multi-microphone signals.
I used R to analyse behavioral data and create vizualisations and Python to analyse EEG data (see my toolbox for EEG processing) and elaborate offline/online signal processing workflow.
At the corner of data science and web developement, I created the skeleton of a neurofeedback app that streamed and transfered the data from the EEG system to a web server in Django and get the data in the browser with web sockets for final feedback display.
Web Development - Full-Stack
- Django/Flask
- Js/React
- Data oriented Web Apps (model deployment, data visualization)
During my PhD, I have developped Web Apps using Django and Javascript for auditory experiments running on computers and tablets. I also worked with NoSQL databases (CouchDB) hosted on a DigitalOcean and PouchDB to build offline-first web app.
I am also using D3 and React to build data vizualisation on the web.
I have created Web Apps using the Web Audio API to create sounds with controled acousticx features (for instance a demo of amplitude and frequency modulations with visualizations).