CV

Damien Aupretre

Student

📞 +33 7 67 91 90 60
✉️ damien.aupretre@student-cs.fr
🐙 TheTrigun99 - github

Education

Master of Engineering — CentraleSupélec (2024 – 2027)

Part of Université Paris-Saclay, ranked #12 worldwide (QS 2024).

CPGE PC* — Lycée Kléber (2022 – 2024)

Admitted to École Polytechnique (ranked #1 in France, top 0.1% of applicants), CentraleSupélec, Mines PSL (Most prestigious engineering schools)
GPA: 4.3 / 4.3

Deutsch-Französisch Gymnasium (DFG-LFA) (2015 – 2022)

Bilingual French-German Abitur : 1.0 (maximum grade)
Specialisation: mathematics, biology, and chemistry

Projects-Experience

Research Papers — Personal Project (2025 - ??)

Getting deep understanding of algorithms by implementing everything from scratch (and reflecting about it [most important part])
Implemented basics deep learning architectures (DiT, Diffusion, VAE, Word2Vec,...)

Kaggle Challenges — Personal Project (2025)

Learned the machine learning basics and Deep Learning basic library and participated in 2 competitions
Predicted accident risk from tabular data using an ensemble of XGBoost, CatBoost, and neural networks.
Built a full ML pipeline covering feature engineering, hyperparameter tuning, and model stacking.

Health Data Science Project — CentraleSupélec (2025)

Analysed high-dimensional multimodal genomic data (gene expression + DNA alteration) from pediatric brain cancer patients to identify tumour-localisation biomarkers.
Implemented and compared multiple sparse classification methods (LASSO logistic regression, Sparse Discriminant Analysis, SGCCA, Multiview), with a focus on the multi-block methods handling joint analysis across data types.
Reduced dimensionality from 15,000+ genomic variables down to a handful of robust, interpretable biomarkers per tumour class.

TIPE, Independent Physics Research Project — Lycée Kléber (2023)

Investigated capillarity and buoyancy effects by varying liquid volumes and surface properties of ping-pong balls.
Modelled ejection dynamics from a water-filled cup using fluid mechanics principles (surface tension, pressure balance).

Skills

Skills

Python (NumPy, pandas, pytorch)
Machine learning/ Deep Learning
R (statistical computing)
Humor

Languages

Languagues

French — Native
German — Fluent (C1-certified)
English — Fluent
Pytorch — Fluent (C1)