Teaching activity and supervision

Recent activity (≥ 2017)

Teaching

2019-20, 2020-21: Convex optimization and dimensionality reduction in Machine Learning (30 hours). International master course of Ecole Polytechnique (Palaiseau, France) given at Mohammed VI Polytechnic University (Ben Guerir, Morocco).

2018-19 to 2020-21: Statistical foundations of Machine Learning (15 hours). Master 2 degree at ISAE/Supaero.

2017-18 to 2020-21: GPGPU computing with CUDA and OpenCL (6 hours). Master 2 degree at ISAE/Supaero.

2017-18 to 2020-21: Image Analysis (36 hours until 2019, then 16 hours). Master 2 in Mathematical Engineering. Université Paul Sabatier.

2018-19: Optimization (12 hours of practical courses). Master 1 degree at Toulouse School of Economics (TSE).

2017-18, 2018-19: Statistics (8 hours of practical courses). Master 2 degree at ISAE/Supaero.

2017-18: Machine Learning (18 hours). Students of various levels from Ho-Chi-Minh city area (M1 students to university lecturers -- course/practicals in the context of a two weeks spring school). VNUHCM - University of Science, Ho-Chi-Minh city, Vietnam.

Ongoing training, technical seminars, and scientific popularization

March 2021: Explainability techniques for Black-Box decision rules in ML. Invited talk at Marseille Astrophysics Laboratory (LAM).

January 2021: Introduction to Pytorch. Courses+practicals of three hours at JDEV-2020. Fully given online.

November 2020: Introduction to Machine Learning. Two courses+practicals of three hours each with Alexandre Boucaud (CNRS Research Engineer, APS, Paris) at JDEV-2020. The first course mainly focuses on the data and the second one on the models. Fully given online.

March 2020: Explainability and Fairness of Black-box decision rules in AI. One hour talk with Ronan Pons (PhD student ANITI) at the Meetup Machine Learning Pau (slides in French).

March 2020: Introduction to Machine Learning. One day ongoing training event for high school lecturers in Toulouse area (course + practicals in Python). Event managed by Yohann Genzmer (lecturer IMT).

March 2020: Explainability and Fairness of Black-box decision rules in AI. 40 minutes talk at the seminar statistics - engineering, gathering applied statisticians from different labs in Toulouse.

October 2019: Explainability and Fairness of Black-box decision rules in A.I. One hour talk at the DEVLOG ongoing training event APSEM2019 (Slides in French: Part 1, Part 2, Part 3).

August 2019: Introduction to Machine Learning. Two hours course and practical at CIMI Recherche-MIDI Summer-camp.

July 2019: 20 hours course and practicals at Master School on Data Science and Geometry.
  • Week 2: Ten hours course and practicals in Machine Learning (slides of day 1: Intro to M.L. / Intro to Python for M.L.).
  • Week 4: Ten hours practicals in (1) Optimal transport for histogram equalization in images, (2) Diffeomorphic image registration with LDDMM, and (3) Neural networks with PyTorch.


November 2018: Introduction to Machine Learning. Two hours talk at the CNRS-INRA ongoing training event (action de formation) APSEM2018 (slides in French).

November 2018: Using TPUs in Deep Learning. One hour seminar at the National Institute for Space and Aeronautics (ISAE-Supaero).

January 2018: Data analysis and Machine learning with Python using the Scikit-learn module - Intermediate level. One day with courses and practicals at Observatoire Midi-Pyrénées.

January 2018: Introduction to GPU computing and OpenCL. Three hours seminar for Master students at the National Institute for Space and Aeronautics (ISAE-Supaero).

July 2017: JDEV 2017 (Development days -- CNRS/INRIA/IRSTEA/INRA/IRD ongoing training event), Marseille. Lecture notes (in French):
  • T7 AP01 (Initiation à Python),
  • T7 A01 (Python Apprentissage),
  • T7 GT02 (Retour d'experience sur OpenCL),
  • T7 GT03 (Python Pandas vs R),
  • T7 plénière (Apprentissage statistique pour la recherche par les données).

April 2017: Python for Scientists - Intermediate level. Three days of courses and practicals at CNRS - Observatoire Midi-Pyrénées. Lecture notes (in French): January 2017: A short introduction to GPU computing and OpenCL. Seminar statistics - engineering, gathering applied statisticians from different labs in Toulouse (slides in French).

Students supervision (last update: September 2020)

2020-21: A. Faure (5th year Paul Sabatier University in computer science - 6 months). Segmentation of 3D medical images using a semi-automatic method and neural networks. Co-supervision with S. Ken (IR INSERM/IRIT, Cancer Institute of Toulouse).

2020-.: L. De Lara (PhD student at Mathematics Institute of Toulouse - Univ. Toulouse - Funded by Ecole Polytechnique). Towards fair and explainable AI. Co-supervision with J.M. Loubes (Pr IMT) and N. Asher (DR IRIT).

2020-.: E. Viala (PhD student at ONERA Toulouse - ISAE-Suparo). Machine Learning models for the analysis of LIDAR images. Co-supervision with N. Rivière abd P.E. Dupouy (ONERA Toulouse)

2020-.: N. Enjalbert-Courrech (M2 SID student in Data Science - Univ. Toulouse - 1 year work-study contract). Valorization of two statistical learning algorithms. Co-supervision with P. Neuvial (CR IMT).

2020: E. Viala (5th year Paul Sabatier University in applied maths - 5 months). Neural Network models for the prediction of pollution impact in atmospheric chemistry. Co-supervision with F. Solmon (CNRS - Laboratoire d'aérologie/OMP)

2020: L. De Lara (5th year Ecole Polytechnique - 6 months). Towards a fair and explainable AI using conterfactual models. Co-supervision with J.M. Loubes (Pr IMT) and N. Asher (DR IRIT)

2020 : I. Zniber (5th year Paul Sabatier University in applied maths - 2 months). Interpretability of neural network decision rules based on multichannel signals .

2020 : J. De La Serna (5th year Paul Sabatier University in applied maths - 2 months). Machine learning models for the analysis of NLP data out of Twitter (github).

2019: E. Letournel and A. Ecoffet (hands on project of Ecole Polytechnique - 10 hours of meetings with the students). Studying the algorithmic bias in predictive algorithms to detect potential discriminations. Co-supervision with J.M. Loubes (Pr IMT/ANITI).

2019: B. Allorant (3rd year ENS Lyon - 2 months). GPGPU solutions to speed-up the estimation of a non-linear 3D PDE. Application to image registration.

2019: A. Gossard (5th year INSA in applied mathematics - 5 months). Denoising and regularization models for the analysis of LIDAR images. Co-supervision with P.E. Dupouy and N. Rivière (ONERA Toulouse)

2019: K. Niang (4th year Paul Sabatier University in applied maths for data mining - 3 months). Definition of a deep learning strategy to predict polution levels based on multimodal satellite information. Co-supervision with F. Solmon (CNRS - Laboratoire d'aérologie/OMP)

2019: E.. Grossiord (Postdoc at IMT - 1 year). Mutli-modal registration of 3D whole-body medical images. Co-supervision with F. Malgouyres (Pr IMT).

2018: V. K. Ghorpade (Postdoc at IMT - 1 year). Registration of 3D whole-body medical images. Co-supervision with F. Malgouyres (Pr IMT).

2018: R. Vaysse (4th year Paul Sabatier University in applied maths for data mining - 5 months). Statistical analysis of data out of speech samples for Parkinson's disease detection. Co-supervision with S. Déjean (IR UPS) and J. Farinas (Mcf UPS - UMR5505)

2018: L. Barros (3rd year IUT Computer Science Toulouse - 3 months). Embedding Python, C++ and R apps with Docker.

2018: L. Riou (2nd year prepa INPT - 6 weeks). GPU optimization of a stochastic algorithm by interfacing R and OpenCL. Co-supervision with Dr. P Neuvial (CR CNRS IMT)

2017-.: C. Champion (PhD student in applied mathematics at INSERM/Mathematics Institute of Toulouse). Development of new strategies for the analysis of complex data. Co-supervision with J.-M. Loubes (Pr IMT) and R. Burcelin (DR INSERM).

2017: V. Brès (5th year student at ENSEEIHT in Applied Maths/Computer Science - 6 months). GPU computing with OpenCL to speed-up large graph clustering algorithms.

2017: S. Lebreton (5th year student at ENSEEIHT in Applied Maths/Computer Science - 6 months). Development of a C++ plugin in 3DSlicer for the semi-interactive segmentation of 3D medical images. Co-supervision with F. Malgouyres (Pr IMT).

2017: N. Artigouha (4th year INSA Toulouse in Computer Science - 2 months). Using the C++ Boost Graph Library to for the analysis of large graphs + Graph visualisation at predefined coordinates in Cytoscape (plugin here).

Older activity (≤ 2016)

Teaching

2016-17: Lectures and practical courses in Image Analysis (8 hours). Master 2 in Mathematical Engineering. Université Paul Sabatier.

2016-17: Practical courses in Statistics (16 hours). Master 2 degree at ISAE/Supaero.

2005-06: Tutorials in Stochastic Process applied to heterogeneous media (16 hours). Master 2 degree in Mechanics. Université Paul Sabatier.

2005-06: Lectures and practical courses in Computational Fluid Mechanics (32 hours). Lecture notes here. The resolution methods for non linear PDEs in 1D and 2D are developed in this lecture. Masters 1 degree in Mechanics. Université Paul Sabatier.

2005-06: Projects in Numerical simulation. Masters degree in mechanics. Université Paul Sabatier.

2005-06: Practical courses in Fluid Mechanics (18 hours). Preliminary degree in Mathematics and Computer Science applied to Sciences. Université Paul Sabatier.

2004-05: Lectures and practical courses in Computational Fluid Mechanics (44 hours). Master 1 degree in Mechanics. Université Paul Sabatier.

2004-05: Project in Numerical simulation (Doubly driven cavity). Masters degree in mechanics. Université Paul Sabatier.

2004-05: Tutorials in Point Mechanics (20 hours). Preliminary degree in Mathematics and Computer Science applied to Sciences. Université Paul Sabatier.

2003-04: Lectures and practical courses in Computational Fluid Mechanics (44 hours). Master 1 degree in Mechanics. Université Paul Sabatier.

2003-04: Tutorials in Point mechanics (20 hours). Preliminary degree in Mathematics and Computer Science applied to Sciences. Université Paul Sabatier.

Ongoing training, technical seminars, and scientific popularization

November 2016: Three applications of data mining. Seminar for Master students at Ecole Nationale Supérieure d'Electrotechnique, d'Electronique, d'Informatique, d'Hydraulique et des Télécommunications (INP ENSEEIHT), Toulouse.

March 2015: Mathematical Engineering, what is that? Seminar to explain to high school students what can be an engineer in applied mathematics -- Formation métier Activités (slides in French. See also the slides of S. Déjean or a document edited by ONISEP).

October 2014: Introduction to Cytoscape for large graphs visualization and analysis. Seminar statistics - engineering, gathering applied statisticians from different labs in Toulouse (slides in French).

July 2014: Introduction to R. Personnel from Université Paul Sabatier. (for more information, see Sébastien Déjean's webpage ).

June 2014: Introduction to statistics. Personnel from Université Paul Sabatier. (for more information, see Sébastien Déjean's webpage ).

January 2014: Introduction to Python for scientists (slides in French). Institut de Mathématiques de Toulouse.

July 2013: Introduction to R. Personnel from Université Paul Sabatier.

June 2013: Introduction to statistics. Personnel from Université Paul Sabatier.

December 2013: Three applications of data mining. Seminar for Master students at Ecole Nationale Supérieure d'Electrotechnique, d'Electronique, d'Informatique, d'Hydraulique et des Télécommunications (INP ENSEEIHT), Toulouse.

March 2013: Using SVN for collaborative projects. Seminar statistics - engineering, gathering applied statisticians from different labs in Toulouse.

Students supervision (last update: September 2020)

2016-2019: T. Trang Bui (PhD student in applied mathematics at INSA Toulouse/Paul Sabatier University). Development of new strategies for the analysis of complex data. Co-supervision with J.-M. Loubes (Pr IMT) and P. Balaresque (CR1 CNRS, AMIS - UMR5288).

2016: D. Grasselly (4th year INSA Toulouse - 3 months - Now student at INSA Toulouse). Development of a Matlab code for the registration of lung images with sliding conditions. Co-supervision with J. Fehrenbach Loubes (Mcf IMT/UPS).

2016: M. Verdier (4th year INSA Toulouse - 3 months - Now student at INSA Toulouse). Development of a Python code for the induction of Bayesian networks from medical data .

2016: A. Martin (3rd year ENS Lyon - 3 months - Now student at ENS Lyon). Development geodesic shooting algorithm for the registration of 3D medical images using OpenCL .

2016: M. Ralle (5th year Univ. Paris Orsay - 4 months - Now aggregate high school lecturer). Statistical analysis of the cochlear coil. Co-supervision with J.M. Loubes (PR IMT/UPS).

2016: S. Roudiere (2nd year prepa INPT - 6 weeks - Now student at Phelma PET Grenoble). Devlopment of non-rigid registration algorithm in Python applied to the motion tracking of US heart images. Co-supervision with Marie-Laure Boizeau (IE INSERM US006 CREFRE, CNRS)

2015: T. Berriat (4th year INSA Toulouse - 3 months Now student at INSA Toulouse). Statistical analysis of the cochlear coil. Co-supervision with J.M. Loubes (PR IMT/UPS) and J. Dumoncel (IE AMIS/CNRS).

2015: A. David (2nd year prepa INPT - 6 weeks - Now student at ENSEEIHT). Devlopment of a GUI in Python to register 3D images.

2015: N. Artigouha (3rd year IUT Computer Science Toulouse - 3 months - Now student at INSA Toulouse). Plugin development in Java to interface R and Cytoscape.

2014: A. Choury (former INSA student - 6 months - Now founder and president of Alykis/consulting). Statistical analysis of seismic wave propagation measures. Co-supervision with J.M. Loubes (PR IMT/UPS) and P. Besse (PR IMT/INSA).

2014: S. Tobji (2nd year IUT informatique Toulouse - 3 months - Now student at Univ. Paul Sabatier/IRIT). Development of a new anisotropic smoothing strategy in ITK. Co-supervision with J. Fehrenbach (McF IMT/UPS).

2013: L. Dolius (M2R Radiophysics and medical imaging Toulouse - 6 months - Now engineer with Cap Gemini Toulouse). Quantitative Analysis of 3D brain images. Co-supervision with C. Fonta (DR CerCo/CNRS) and M. Mescam (McF CerCo/UPS).

2010: A. Camphuis (M1 Supelec - 2 months - Now Petroleum Engineer with Perenco). Validation of an image registration algorithm. Co-supervision with F.X. Vialard (Former postdoc Imperial College London / now McF Paris Dauphine).

2009: D.P. Zhang (PhD student - unformal supervision - Now with Exascale Computing/AMD Research Group). Motion correction of coronary vessels in CT images. Main supervisor: D. Rueckert (Pr Imperial College London).

2008: A.L. Fouque (M2R ENS Cachan - 5 months). Analysis of the BOLD signal in fMRI. Main supervisor: P. Ciuciu (CR CEA Saclay).

2005: V. Gratsac (M2 Computer Science Univ. Nantes - 6 months - Now engineer with SYNEIKA, Rennes). Tensor voting for large vascular network images. Main supervisor: F. Plouraboue (DR IMFT/CNRS).

2004: G. Gujadur (L3 Mecanics - 3 months - Now at Siemens Industrial Turbomachinery AB, Sweden). Quantitative analysis of the vascular network in synchrotron images. Main supervisor: F. Plouraboue (DR IMFT/CNRS).