Bio

I pursued a PhD in machine learning for health data supervised by Danilo Bzdok (McGill, Canada) and Danielle Basset (UPENN, USA). I received intensive training in machine learning and brain imaging working in collaboration with Gaël Varoquaux (INRIA, Paris, France) and Simon Eickhoff (Düsseldorf, Germany). Being supervised by academics from very different fields (medicine, computer science, and physics) really made clear that I have a deep interest for combination of rigorous methodology and innovating approach to knowledge extraction. Next, during postdocs at Chi-Chun Lee's NTHU (BIIC lab) in Taiwan and at INSERM (Comete lab) with Leslie Decker in France, I focused on leveraging statistical learning to predict transition to Alzheimer's disease using MRI. Following the reproducibility crisis, I recently joined INRIA (EMPENN team) to work on statistical results reproducibility with Camille Maumet and Thomas E Nichols (Oxford Big Data Institute, UK).

Work experience

Since 2023	Researcher · Postdoc @ INRIA (IRISA lab, EMPENN team), Rennes  #Statistics #SignalProcessing #Reproducibility
2021-2022	Researcher · Postdoc @ INSERM (COMETE lab), Caen  #MachineLearning #SignalProcessing
2019-2020	Researcher · Postdoc @ NTHU (BIIC lab), Taiwan 🇹🇼  #DeepLearning #SignalProcessing

Education

2015-2019	Ph.D in Health Data Analysis (Magna Cum Laude) · RWTH university, Aachen, Germany 🇩🇪 [RWTH library publication] [PDF]  #MachineLearning #Statistics #Neuroimaging #Bigdata #HealthData
2013-2015	Master in Neurosciences (with honors) · University of Tours  #Statistics #Brain #Psychiatry + Psychologist title, supervision by the Master "Child psychology" · University of Tours
2010-2013	Bachelor in Psychology (with honors) · University of Tours + 3rd year · Bucknell University, Lewisburg, USA 🇺🇸