AI Research Engineer with a strong background in Data Science and Statistics.
Currently in my final year of a double MSc. degree.
Benchmark of Graph Neural Network (GNN) Repo
- Organization: Ecole Polytechnique - IP Paris
- Course: Machine Learning Research Seminar (E. Flamary / E. Moulines)
- Description: Implementation of a GNN research Benchmark including the latest MEWIS pooling, as described in "Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks"URL
Text Mining and Health Care Pathway Repo
- Organization: Assistance Publique - Hôpitaux de Paris (Paris, FRA)
- Duration: November 2022 - May 2023 (6 months)
- Description: Conducted a project on "A Novel Methodological Framework for Analyzing Health Trajectories and Survival Outcomes in Heart Failure Patients". The aim was to study the care pathways of heart failure patients through NLP and sequential pattern mining, then implement a survival analysis model.
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MSc. in Data Science at Ecole Polytechnique - IP Paris (FRA)
- 2023-2024
- Focus on Deep Learning, Statistical Learning Theory, Privacy, GenAI, MCMC Methods.
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MSc. in Statistics and Economics at ENSAE Paris - IP Paris (FRA)
- 2022-2024
- Focus on Statistics, Machine Learning, and Deep Learning.
- Also studied Advanced Econometrics, Macroeconomics, Microeconomics.
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MSc. in Engineering at Telecom SudParis (FRA)
- 2020-2024
- Achieved the title of "Ingénieur Télécommien" (general engineering degree) with expertise in Data Science, Big Data, and Numerical Analysis.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent