CV
Education
- PhD in Statistics Machine Learning (2012–2016)
- University Pierre and Marie Curie
- title: Segmentation of Counting Processes and Dynamical Models
- Thesis defended on June 27th 2016 before a jury composed of: Pierre Alquier (ENSAE), Examiner; Sylvain Arlot (Univ. Paris-Sud), Examiner; Gérard Biau (UPMC), Examiner; Stéphane Gaïffas (Univ. Paris Diderot), Advisor; Agathe Guilloux (Univ. Evry), Advisor; Erwan Le Pennec (École Polytechnique), Reviewer
Manuscript, 
Slides
- MSc in Applied Mathematics, speciality Statistics (2011–2012)
- University Pierre and Marie Curie
- Master’s Thesis: Change-Points Detection with Total-Variation Penalization
- Under the supervision of Stéphane Gaïffas (Univ. Paris Diderot) and Agathe Guilloux (Univ. Evry)
- Manuscript
- MSc in Applied Mathematics, speciality Probabilities and Random Models (2010–2011)
- University Pierre and Marie Curie
- Master’s Thesis: Poisson Access Networks with Shadowing: Modeling and Statistical Inference
- Under the supervision of Bartlomiej Blaszczyszyn (INRIA) and Mohamed Karray (Orange Labs)
- Manuscript, Slides
- Magistère Mathématiques (2008–2010)
- University Gabes, Tunisia
- Master’s Thesis: Backward Stochastic Differential Equations and Financial Mathematics
- Under the supervision of Said Hamadène (Univ. Le Mans) and Ibtissem Hdhiri (Univ. Gabes)
- Manuscript, Slides
- BSc in Mathematics (2005–2007)
- University Gabes, Tunisia
Work experience
- Assistant Professor (2020–)
- LMAC Laboratory
- University of Technology of Compiègne
- Postdoctoral Researcher (2019–2020)
- LITIS Laboratory
- University Rouen Normandy
- Postdoctoral Researcher (2017–2018)
- Laureate Postdoctoral Fellowship of Dim Math Innov Program
- Modal’X Laboratory
- University Paris Nanterre
- Temporary Teaching and Research Assistant (2016–2017)
- Modal’X Laboratory
- University Paris Nanterre
- Temporary Teaching and Research Assistant (2016–2017)
- Modal’X Laboratory
- University Paris Nanterre
- Teaching Assistant (2012–2015)
- Theoretical and Applied Statistics Laboratory
- University Pierre and Marie Curie
Skills
- Software Engineering
- Python (2/3), Jupyter Notebook, R, Matlab
- Python Libraries
- Scikit-Learn, Pandas, Numpy, Scipy, Matplotlib, Cython, TensorFlow, PyTorch
- System Administration
- GNU/Linux, MacOS X , Git, PyCharm
- Desktop Publishing
- $\LaTeX$
Publications
Talks
Apprentissage pour l’Intensité d’Événements avec Points de Rupture
46èmes Journées de Statistique de la SFdS, Rennes, France
Learning the intensity of time events with change-points
Work Group of Statistics PhD Students, LSTA-UPMC, Paris, France
Binarsity: Prédiction en Grande dimension via la Sparsité Induite par la Binarisation de Variables
47èmes Journées de Statistique de la SFdS, Lille, France
Learning high-dimensional time-varying Aalen and Cox models
48èmes Journées de Statistique de la SFdS, Montpellier, France
Around Supervised Learning with Weighted Total-Variation Penalization
Seminar of Madal'X, University Paris Nanterre, Nanterre, France
Complétion Jointe de Matrices
50èmes Journées de Statistique de la SFdS, Paris, France
Collective Matrix Completion
4th International Society for NonParametric Statistics, Salerno, Italy
Binarsity: a penalization for one-hot encoded features in linear supervised learning
Seminar of LumenAi Startup, Paris, France
Binarsity: a penalization for one-hot encoded features in linear supervised learning
AgroParisTech Seminar, Paris, France
Screening Sinkhorn Algorithm for Regularized Optimal Transport
GdR ISIS/MIA Meeting, CNRS, France
Screenkhorn: Screening Sinkhorn Algorithm for Regularized Optimal Transport
Summer School on Applied Harmonic Analysis and Machine Learning, Genoa, Italy
Binarsity : New Penalization for Supervised Learning
Séminaire CREST ENSAI, Zoom-Seminar
Screenkhorn: New Algorithm for Regularized Optimal Transport
Séminaire CMAP École Polytechnique, Zoom-Seminar
An application of Optimal Transport in Data Science
Séminaire Science de données de l’UTC, Zoom-Seminar
Prédiction via la sparsité induite par la binarisation de variables
Séminaire Probabilités et Stats du LMM, Le Mans Université, Zoom-Seminar
Collective Matrix Completion
Séminaire Groupe de travail Machine Learning and Massive Data Analysis, Centre Borelli ENS-PARIS SACLAY, Centre Borelli, ENS Paris Saclay
Binarsity
Journées MAS 2022 de SMAI, Rouen, France
PUOT: Partial Optimal Transport with Applications on Positive-Unlabeled Learning
SIAM conference on Mathematics for Data Science, Hybrid Conference
L’IA au LMAC, Sciences de Données avec Transport Optimal
Journée Scientifique, chaire industrielle SAFE AI, UTC
Teaching
A12/ Probability and Statistics
S13/ Algebra and Geometry
A13/ Linear Models II
S14/ Algebra and Geometry
A15/ Times Series
S16/ Mathematical Statistics
A16/ Real Analysis and C2I Certificate
S17/ Statistics
A20/A21/ Algébre Linéaire et Applications
A21/ Eléments de probabilités
S22/ Fonctions de plusieurs variables réelles et applications
A22/ Révisions d’analyse et d’algèbre
A22/A23/ MT02 - Analyse réelle 1
S21/S22/S23/S24 Machine Learning
A24 Algébre Linéaire et Applications