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Johann Faouzi



My name is Johann Faouzi and I am a postdoctoral research fellow at Paris Brain Institute, Paris, France. My main research interest is machine learning, with applications to neuroscience and open source software. My PhD thesis was about predicting impulse control disorders in Parkinson's disease. Impulse control disorders are psychiatric disorders characterized by difficulty in self-control of emotions, thoughts and behaviors. These disorders are common in Parkinson's disease and associated with impaired quality of life for patients and increased burden for caregivers. We investigated the predictability of these disorders from associated or suggested clinical and genetic risk factors by training machine learning algorithms. We also investigated the genetics of these disorders using genetic risk scores. Finally, in a more methodological work, we investigated the integration of time-independent data (such as genetic data) in recurrent neural networks. I also had the opportunity to work on several other projects with many people, including several literature reviews (one on deep learning for brain disorders, one on impulse control disorders in Parkinson's disease, one on machine learning for Parkinson's disease and related disorders, and one on the prediction of mild cognitive impairment in Alzheimer's disease using machine learning), as well as other studies on machine learning applied to neuroscience (a challenge on brain-age prediction and a study on functional brain connectivities in Tourette disorder). I am also interested in machine learning for time series. I have created a Python package dedicated to time series classification and contributed to other open source Python packages (not necessarly on time series). I am a strong believer of the importance of good programming practices, in particular for people working in academia (both professors and researchers).


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Comparison of mean diffusivity, R2* relaxation rate and morphometric biomarkers for the clinical differentiation of parkinsonism

Lydia Chougar , François-Xavier Lejeune , Johann Faouzi , Benjamin Morino , Alice Faucher
Parkinsonism & Related Disorders, 2023, 108, pp.105287. ⟨10.1016/j.parkreldis.2023.105287⟩
Journal articles hal-04041736v2
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Machine learning-based prediction of impulse control disorders in Parkinson's disease from clinical and genetic data

Johann Faouzi , Samir Bekadar , Fanny Artaud , Alexis Elbaz , Graziella Mangone
IEEE Open Journal of Engineering in Medicine and Biology, 2022, 3, pp.96 - 107. ⟨10.1109/OJEMB.2022.3178295⟩
Journal articles hal-03680714v2
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Multivariate classification provides a neural signature of Tourette disorder

Giuseppe A Zito , Andreas Hartmann , Benoît Béranger , Samantha Weber , Selma Aybek
Psychological Medicine, 2021
Journal articles hal-03480739v1
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Impulse control disorders and related behaviors in Parkinson's disease: risk factors, clinical and genetic aspects and management

Johann Faouzi , Jean-Christophe Corvol , Louise-Laure Mariani
Current Opinion in Neurology, 2021, Publish Ahead of Print, ⟨10.1097/WCO.0000000000000955⟩
Journal articles hal-03298526v1
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Deep learning for brain disorders: from data processing to disease treatment

Ninon Burgos , Simona Bottani , Johann Faouzi , Elina Thibeau-Sutre , Olivier Colliot
Briefings in Bioinformatics, 2021, 22 (2), pp.1560-1576. ⟨10.1093/bib/bbaa310⟩
Journal articles hal-03070554v1
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Exploratory analysis of the genetics of impulse control disorders in Parkinson's disease using genetic risk scores

Johann Faouzi , Baptiste Couvy-Duchesne , Samir Bekadar , Olivier Colliot , Jean-Christophe Corvol
Parkinsonism & Related Disorders, 2021, 86, pp.74 - 77. ⟨10.1016/j.parkreldis.2021.04.003⟩
Journal articles hal-03298502v2
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Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic, Quantitative and Critical Review

Manon Ansart , Stéphane Epelbaum , Giulia Bassignana , Alexandre Bône , Simona Bottani
Medical Image Analysis, 2021, 67, pp.101848. ⟨10.1016/⟩
Journal articles hal-02337815v2
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pyts: A Python Package for Time Series Classification

Johann Faouzi , Hicham Janati
Journal of Machine Learning Research, 2020, 21, pp.1 - 6
Journal articles hal-02883389v1
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Automated Categorization of Parkinsonian Syndromes Using Magnetic Resonance Imaging in a Clinical Setting

Lydia Chougar , Johann Faouzi , Nadya Pyatigorskaya , Lydia Yahia‐cherif , Rahul Gaurav
Movement Disorders, 2020, ⟨10.1002/mds.28348⟩
Journal articles hal-03046578v2
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Ensemble Learning of Convolutional Neural Network, Support Vector Machine, and Best Linear Unbiased Predictor for Brain Age Prediction: ARAMIS Contribution to the Predictive Analytics Competition 2019 Challenge

Baptiste Couvy-Duchesne , Johann Faouzi , Benoît Martin , Elina Thibeau-Sutre , Adam Wild
Frontiers in Psychiatry, 2020, 11, ⟨10.3389/fpsyt.2020.593336⟩
Journal articles hal-03136463v1
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Tslearn, A Machine Learning Toolkit for Time Series Data

Romain Tavenard , Johann Faouzi , Gilles Vandewiele , Felix Divo , Guillaume Androz
Journal of Machine Learning Research, 2020, 21, pp.1 - 6
Journal articles hal-02883390v1
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Predicting Impulse Control Disorders in Parkinson's Disease: A Challenging Task

Johann Faouzi , Samir Bekadar , Olivier Colliot , Jean-Christophe Corvol
International Congress of Parkinson's Disease and Movement Disorders, Sep 2019, Nice, France
Conference papers hal-02315533v1
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Classic machine learning algorithms

Johann Faouzi , Olivier Colliot
Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023
Book sections hal-03830094v4
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Machine learning for Parkinson’s disease and related disorders

Johann Faouzi , Olivier Colliot , Jean-Christophe Corvol
Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_26⟩
Book sections hal-03830073v2
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Time Series Classification: A review of Algorithms and Implementations

Johann Faouzi
Ketan Kotecha‬. Machine Learning (Emerging Trends and Applications), Proud Pen, In press, 978-1-8381524-1-3
Book sections hal-03558165v1