Teaching

Supervised PhD Students

Junwoo Park. Machine learning for microscopy data. Co-supervised with J. Miné-Hattab, EDITE PhD school, 2023 -
Margot Hérin. Explainable sparse models: a marriage between machine learning and decision theory. Co-supervsied with P. Perny. SCAI grant. 2021 -
Arsen Sultanov. Generation of novel crystallographic structures for the energy storage using statistical machine learning. Co-supervised with J.-C. Crivello and T. Rebafka. Grant: 80|Prime programme. 2021 -
Ariane Marandon. Graph embedding and clustering: new decision rules for personalized medicine. Grant: DIM Math Innov (https://www.dim-mathinnov.fr/). Co-supervised with T. Rebafka et E. Roquain, LPSM, Sorbonne university. 2020 - 2023.
Elie el Hachem. Patients stratification from graphs. Grant of PhD School 394. Co-supervised with H. Soula, Sorbonne university. 2020 - 2023.
Adèle Weber. Metabolic networks modelling (from gut flora microbiome) using multi-omic approaches. Grant of PhD School 394. Co-supervised with H. Soula, Sorbonne university, 2018 - 2021.

Nguyen Thanh Hai. Some contributions to deep learning applied to metagenomic data. Co-supervised with J.-D. Zucker and E. Prifti, 2015 – 2018.

Junwoo Park. Master 2 BIM. Machine learning for microscopy data. Co-supervised with J. Miné-Hattab, 2023
Arsen Sultanov. Master 2, Statistics, SU. Generation of crystallographic structures using machine learning. Co-supervised with J.-C. Crivello and T. Rebafka, 2021
Elie el Hachem, Master M2 BIP, SU. Integration of single cell data, co-supervised with H. Soula, 2020
Ariane Marandon. Master M2 Learning and Algorithms, SU. Metabolic graphs clustering, co-supervised
with T. Rebafka, E. Roquain, 2020.
Antoine Gagelin. Master M2 BIM. Deep learning to reconstruct social networks, co-supervised with H. Soula
(Sorbonne University), 2019.
Adèle Weber. Master M2 BIM. Metabolic network reconstruction and structure analysis and their correlation to environmental phenotypes. Co-supervised with H. Soula (UPMC), 2018.

Asma Nouira. M2 Systèmes Intelligents Communicants (SIC), Ecole Nationale d'Ingénieurs de Sousse ENISo. Generative Adversarial Networks to discover new crystallographic structures. Co-supervised with J.-C. Crivello (ICMPE Institut de chimie et des materiaux Paris-Est), 2018.

Maria-Virginia Ruiz. Master M2 BIM, UPMC. A machine learning approach to analyse complex causal interactions. Co-supervised with P.-H. Wuillemin (LIP6), 2017

Olga Permiakova. Master M2 BIM, UPMC. A Machine Learning Approach to Study Complex Causal Interactions, 2016.

Yuejun Liu. Master M2 Public Health, University Paris XI. Prediction of Diabetes Remission and Glucose Intolerance Evolution in Obese Subjects Post Bariatric Surgery. Co-supervised with J. Aron-Wisnewsky, 2016

Thibaut Lajoie-Mazenc. Ecole polytechnique -- 3rd year. Statistical Machine Learning for Understanding Diabetes Remission, 2015.

Samuel Lalam and Junwoo Park. M1, BIM, SU. Machine learning methods for scRNA-seq data. Co-supervised with J. Bernardes, 2021
Oktawia Scibior. M1 BIM, SU. Using Machine Learning to study Long-Term Effects of a Dietary Intervention, 2020
Ibrahima Sene, Rayan Bitar (binome). M1 BIM, Analysis of proteomics data, 2019
Boukherissa Amira. M1 BIM. Temporal metabolomic data processing, 2020

Yasser Mohseni Behbahani. Master BIM M1 and summer 2018 internship. Machine learning for interpretable models, 2018.
H. Hosni, M. Garsaa. M1 BIM, Tryptophan Kynurenine Pathway and Bariatric Surgery. Exploratory Data Analysis, UPMC. Co-supervised with H. Soula (UPMC), 2017
W. Jrad. M1 BIM, Deep learning for biomedical image processing, co-supervised with Y. Chevaleyre, 2017.
Traore Bassiro and Ibrahima Camara. Master M1 BIM, UPMC. Exploratory Analysis of Biomedical Heterogeneous Data, 2016.
Bishnu Sarker. Master M1 DMKM, UPMC. Data mining and applications of supervised learning to realistic biomedical problems, 2015.

Data structures and C programming (L2, 2012 - 2015)
Elements of object-oriented programming with Java (L2, 2012 - 2017)
Elements of programming 1, Python (L1, 2016 - 2022)
Programming for scientific computations, Fortran (L2, 2012 - 2019)
Statistics, classification and data mining (M2, 2014 - )
Programming and human-computer interfaces (L2, 2016 - 2017)
Cellular ecosystems: from the modelling to therapeutic treatment (M2, 2014 - )
Statistical machine learning for medical applications (M2, 2019 - )
Data mining for complex data: genomics, transcriptomics (M2, 2012 - 2014)
Data structures and advanced C programming (L2, 2019 - 2020)
Data analysis tutorat (M1, 2014 - 2015)
Algorithms and data structures for biology (L2, 2020 - )
Mathematics and statistics for biology (L2, L3, 2022 - )