Copyright © 2022 Aurele DALIBOT
Myself
Hi, my name is Aurele, I am a Machine Learning Engineer at the European Space Agency, passionate about new technologies, innovations and AI. I am currently looking for a job opportunity as machine learning engineer or as data scientist.
About Me
My name is Aurele, I come from Paris, I am a Machine Learning Engineer at the European Space Agency, in the CAVES & PANGAEA teams.
I have recently been graduated from the Imperial College London with the highest distinction for an MSc in Advanced Computing, where I have attended the following modules :
- Advanced Computer Architecture
- Advanced Computer Security
- Computational Finance
- Cryptography Engineering
- Deep Learning
- Principles of Distributed Ledgers
- Reinforcement Learning
- Software Engineering for Industry
This master was part of a double degree with Centrale Nantes, where I will be graduated in April 2022. I am looking for an opportunity in which I could make the most of my computing and AI skills, as well as my deep interest for machine learning models development and new technologies.
Oct 2021 - Apr 2022, European Space Agency (ESA)
Machine Learning Engineer, Paris, France
Development of machine learning algorithms for recognition of planetary materials from multispectral datasets. The goal is to allow astronauts to automatically guess the rocks or minerals they discover on new planets, using spectrometers. Thus, I am developing algorithms for spectral unmixing of RAMAN or VNIR spectra. Implementing new modules for the current project. Working in collaboration with researchers on a paper to publish (Spectral Unmixing technology).
Apr 2021 - Sept 2021, Imperial College
MSc Project, London, United Kingdom
Development of a lipreading application using Pytorch and OpenCV for patients that have received a tracheostomy and cannot speak anymore. Developed word lipreading models and sentence lipreading models using a Transformer architecture. Developed an efficient liptracking pipeline for real-time predictions. Code available here.
Summer 2020, Thales
Data Scientist Intern, Rungis, France
Worked with the innovation team on a predictive maintenance platform. The idea was to monitor the servers responsible for the aerial surveillance and to predict a future outage of the servers, in order to reboot the system before it happens. Implemented deep learning algorithms for outage prediction, using CNN, LSTM and GRU networks and conducted tests on the existing platform. My contribution was to enhance the existing models, using fine-tuning methods and the implementation of a module for memory monitoring. I was able to predict memory leaks.
Autumn 2019, Nantes Hospital
Software Developer Project, Nantes, France
Developed application software to control an automatic robot Implemented a video tracking software with the OpenCV library to track the surgeon tools, in order to move the camera.