CV
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Contact Information
| Name | Seydina Ousmane NIANG |
| Professional Title | PhD Student in Applied Mathematics |
| ousmaneniangprs@gmail.com | |
| Phone | +33 7 86 68 29 77 |
| Location | Nice, Provence-Alpes-Côte d'Azur |
| Website | https://sniang02.github.io |
Professional Summary
PhD student in applied mathematics at Université Côte d’Azur, specialising in deep probabilistic graphical models for the joint analysis of networks and continuous data. Member of the INRIA MAASAI team.
Experience
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2023 - PhD Researcher
INRIA – Équipe MAASAI / Laboratoire J.A. Dieudonné
Deep generative models for the joint analysis of networks and continuous data.
- Deep latent variable models for network analysis
- Variational inference and graph neural networks
- Collaboration with INRIA MAASAI team
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2022 - 2022 Research Intern – Deep Learning: Neural Differential Equations
Laboratoire de Mathématiques d'Orsay (LMO)
Research internship on Neural Differential Equations applied to pharmacokinetics modelling.
- Neural Differential Equations
- Pharmacokinetics modelling
- Tools: PyTorch, torchdyn, PyTorch Lightning
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2020 - 2020 Supervised Research Work
Université Paris-Saclay
Study of free groups on any set X and properties of their subgroups.
- Group theory
- Free groups and subgroup properties
Education
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2023 - Nice, France
PhD
Université Côte d'Azur
Applied Mathematics
- Deep generative models for the joint analysis of networks and continuous data
- Supervisors: Prof. Charles Bouveyron, Dr. Marco Corneli, Prof. Pierre Latouche
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2022 - 2023 Paris, France
M2 (Master 2)
École Polytechnique / Université Paris-Saclay
Mathematics and computer sciences – Artificial Intelligence
- Deep Learning
- Reinforcement Learning
- Statistical Learning
- Optimization
- Big Data
- Graph Theory
- NLP
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2021 - 2022 Paris, France
M1 (Master 1)
Université Paris-Saclay / ENSTA PARIS
Applied Mathematics
- Statistics
- Optimization
- Machine Learning
- Probability
- Time Series
- Operational Research
- Deep Learning
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2020 - 2021 Paris, France
DU Magistère
Université Paris-Saclay
Pure Mathematics
- Probability
- Statistics
- Dynamical Systems
- Algebra
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2020 - 2021 Paris, France
Double bachelors
Université Paris-Saclay
Mathematics and Computer Science (Double Bachelor)
- Mathematics
- Computer Science
Publications
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2026 The Deep Latent Position Block Model for the Clustering of Nodes in Multi-Graphs
Preprint (HAL)
Extension of the Deep-LPBM to multidimensional networks using a deep VAE with GCNs.
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2025 The Deep Zero-Inflated Latent Position Block Model for the Clustering of Nodes in Graphs
Preprint (HAL)
Deep generative model for node clustering in sparse networks with zero-inflated structure.
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2025 Importance Weighted Directed Graph Variational Auto-Encoder for Block Modelling of Complex Networks
Preprint (HAL)
First importance-weighted graph VAE for weighted and directed network clustering.
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2024 Conditional Denoising Diffusion Probabilistic Models for the Clustering of Images
JDS 2024 – 55e Journées de Statistiques de la SFdS
Conditional DDPM extension for image clustering via a variational EM algorithm.