Resume

Theo Lepage

Ph.D. student in A.I. → Self-Supervised Learning for Speaker Recognition

Education

Sorbonne Université (Ph.D. in Artificial Intelligence)

Paris, France

Nov. 2022 - Nov. 2025

Conducting research related to "Learning speech and speaker representations for robust speaker and language recognition"
Supported by French ANR 'APATE' project (Forensic Deepfakes Detection Toolbox)
Supervised by Dr. Réda Dehak and Pr. Thierry Géraud (LRE-EPITA)

Paris, France

Sep. 2017 - Sep. 2022

Signal processing and machine learning (IMAGE major) + scientific research specialization (RDI major)

Experience

Research Scientist Intern at Siemens Healthineers

Princeton, USA

Feb. 2022 - Sep. 2022

Focused on state-of-the-art deep learning models for MR images enhancement (denoising and super-resolution)
Designed a CNN architecture that leverages the attention mechanism of Vision Transformers and recovers more details compared to the solution being used in the product

Research Student at LRE

Paris, France

Jan. 2020 - Jan. 2022

Worked on self-supervised methods applied to speaker and language recognition while doing monthly "lightning" talks about my progress (supervised by Dr. Réda Dehak)
Developed a label-efficient non-contrastive speaker verification model that outperforms its supervised counterpart when fine-tuned with only 2% of labeled data
Our work led to a publication and an oral presentation at Interspeech 2022 (one of the top conferences in the field)

Software Developer Intern at CNRS

Paris, France

Sep. 2020 - Jan. 2021

Contributed to a real-time digital holography software (C++ / CUDA) used for retinal blood flow analysis in a medical setting
Our work resulted in a 20x (500 to 10,000 FPS) speedup which improved substantially output images contrast and quality
Our refactoring and the addition of unit tests improved the stability and allowed the project to become open source
Founding member of the association 'Digital Holography' created to sustain the development of the software