Pingouin
Pingouin is an open-source Python package for statistics. It is built on top of Pandas and NumPy and provides high-level functions to perform the most common statistical tests. Learn more on the documentation or check the code on GitHub
I am a neuroscientist and sleep researcher in the Center for Human Sleep Science at the University of California, Berkeley.
My research examines how sleep — or the lack of it — impacts human health. My work has been featured in several news media and podcasts (e.g. New York Times, This Is Your Brain).
In addition, I joined Oura in 2020 as a data science and sleep advisor. There, I have been co-leading the development of the next generation of sleep algorithms.
Beyond sleep, my domains of expertise include machine learning & signal processing, in particular when applied to polysomnography and/or wearable physiological data (e.g. EEG, ECG, PPG, HRV).
Part of my research aims at discovering new sleep biomarkers of various human diseases — including diabetes, atherosclerosis and Alzheimer's disease.
I am also a firm believer of open science. I am the creator and core maintainer of several open-source libraries in Python,
which are now being used by thousands across the globe:
Pingouin (statistics, +500k downloads & taught in several universities),
YASA (automatic sleep staging) and
AntroPy (complexity of time-series).
When I am not working, you can find me enjoying precious moments with my amazing wife and daughter, playing music, or hiking with friends in beautiful California.
Academics
| 2018-Present | Postdoctoral researcher, Center for Human Sleep Science (Walker lab), University of California, Berkeley |
| 2014-17 | PhD in Neuroscience, with honors, Lyon 1 University, France | 2012-14 | Master degree in Neuroscience, cum laude, Lyon 1 University, France |
| 2009-12 | Bachelor degree of Cognitive Sciences, summa cum laude (ranked 1st), Lyon 2 University, France |
| Software development | Python, R, Matlab, cloud-computing, Git, Docker |
| Signal processing | Polysomnography (EEG, EKG), structural and functional MRI, accelerometer, photoplethysmography (PPG), heart rate variability (HRV) |
| Data science | Machine-learning, statistical modeling, data processing and visualization |
| Machine-learning in Python, graduate level (UC Berkeley) |
| Mentoring of several undergraduate and postgraduate students (UC Berkeley) |
| Neurobiology, undergraduate level (Lyon University) |
| Ethics in medicine, medical school (Lyon University) |
| Neuro-imaging (fMRI), graduate level (Lyon University) |
Publications
Please find below a list of selected publications (last updated June 2022)
PDF versions are provided for individual, noncommercial purposes only. These files may not be reposted without permission. Copyright and all rights therein resides with the respective copyright holders, as stated
within each paper.
Media outreach
Software development
Please visit my GitHub repository for an exhaustive list of the projects/softwares that I am contributing to.
YASA
YASA (Yet Another Spindle Algorithm) is an open-source Python package for sleep analysis. It implements several state-of-the-art and validated algorithms to score sleep stages, detect spindles & slow-waves, and calculate features from sleep polysomnography recordings. Learn more on the documentation or check the code on GitHub
AntroPy
AntroPy is an open-source Python package for computing several entropy & complexity metrics of time-series. Learn more on the documentation or check the code on GitHub.
Tutorials
Please find below some tutorials regarding the analyses I specialize in.
The Science of Dream Recall
Why do some people remember more of their dreams?
Correlation(s) in Python
A primer on correlation and significance testing between two or more variables in Python.
EEG bandpower
Compute the average bandpower of an EEG signal in Python.