Bio
I am a Master's degree student in Mathematics, Machine Learning & Computer Vision at the master
MVA from ENS Paris-Saclay. I previously graduated
from École Centrale de Lyon with an engineering degree in Applied Mathematics.
During my engineering degree, I also obtained a BSc in Mathematics and an MSc in Applied Mathematics from Lyon 1 University.
I would like to pursue my studies with a PhD in Computer Vision! I am curious about many research directions in CV and have recently enjoyed working with M. Aubry in the Imagine team at ENPC on unsupervised and weakly-supervised problems with applications in text-line analysis.
Short resume
Research experiences
| Summer 2022 | 5-month research internship advised by Pr. M. Aubry in the Imagine team at ENPC Subject: Weakly-supervised methods for Text-line analysis. |
| Summer 2021 | 3-month research internship advised by Pr. E. Dellandrea at CNRS LIRIS Subject: Real-time Visual Scene Understanding for Robotics. |
Education
| 2022 - 2023 | Master's Degree Mathematics, Vision and Learning (MVA) at ENS Paris-Saclay |
| 2019 - 2022 | French Engineering degree in Applied Mathematics at École Centrale de Lyon |
| 2017 - 2019 | French preparatory classes at Lycée Marcelin Berthelot |
Double curriculums in Applied Mathematics followed during my engineering degree at École Centrale de Lyon:
| 2021 - 2022 | MSc MeA in Applied Mathematics at Lyon 1 University with track Vision, Image & Learning |
| 2020 - 2021 | BSc in General Mathematics at Lyon 1 University |
Projects
-
Weakly-supervised Deep Learning methods for text-line analysis with Y. Siglidis
and N. Gonthier.
Advisor: Pr. M. Aubry (Imagine team, ENPC).
More informations (Github and preprint) to be released soon!
-
Object detection and 6D pose estimation for real-time Robotics.
Advisor: Pr. E. Dellandrea (CNRS LIRIS).
3-month research internship on the Robotics project Chiron in the LIRIS team (2021). I was in charge of the literature review on real-time object detection and 6D pose-estimation. I delivered: Report (french), Github- a 40 pages literature report over Deep Learning algorithms for Object detection & Pose Estimation,
- a ready-to-use baseline for the project (FS-Net, CVPR'21).
-
Sparse variable selection in Lasso with Knockoffs with Jérémie Marlhens.
Advisor: Pr. Y. de Castro (Institut Camille Jordan).
Academic research project during second term of last year (2021-2022) at École Centrale de Lyon. We studied the control of False Discovery Rate via Knockoffs as proposed by R. Barber and E. Candès in their 2015 article. We delivered a 25-page report that details the proof presented in the article and shows applications to System identification.
Report
-
Incremental Deep Learning with Clément Martinelli.
Advisor: Pr. E. Dellandrea (CNRS LIRIS).
Academic research project during 2nd year (2020-2021) at École Centrale de Lyon. We studied Incremental Learning techniques to alleviate catastrophic forgetting when training an already trained Deep Neural Network on new examples or tasks. We delivered a 50-page report over core existing techniques and proposed a theoretical improvement of one of them (GEM).
Report (french)