About Me
I am a PhD student in Artificial Intelligence working on “Deep Learning for Text Simplification using Unsupervised Multilingual Approaches” at Facebook AI Research and Inria.
Download my detailed resumé.
Interests
- Artificial Intelligence
- Natural Language Processing
- Language Modeling
- Text Simplification
Education
PhD in Artificial Intelligence, 2021
Facebook AI Research & Inria
Master of Science in Mathematics, Vision and Machine Learning (MVA), 2017
Ecole Normale Supérieure Paris-Saclay
Master of Engineering in Applied Mathematics, 2017
École Centrale Paris
Experience
PhD Student
- Created a demo based on my research in Text Simplification that was presented to Mark Zuckerberg. It was also showcased by Facebook’s CTO at the company-wide All Hands conference, in front of 15k employees.
- My research involved challenging large-scale engineering skills: I trained CamemBERT Language Model in parallel on 256 GPUs on 138GB of training text, I scaled my text mining pipeline using neural semantic embeddings to up to 1 billion sentences by optimizing disk IOs, CPU preprocessing and GPU nearest neighbor search, all of this on up to 1000 GPUs with preemption-aware logic.
- My latest text simplification method achieves state-of-the-art results on all simplification benchmarks while being unsupervised.
- Integrated my code and models into Facebook’s codebase and infra. My code is currently being ported in production.
- Major success of the release of our open-source CamemBERT model (>20k downloads/month, industry applications.
- Presented my research in person to the French Minister for People with disabilities (my research is core to the Cap’FALC project, involving the French Government, UNAPEI association, Inria and FAIR).
- My work was featured in 9 news articles/podcasts, I gave 3 interviews (VentureBeat, Le Monde, France Culture, ActuIA, …).
NLP Research Intern
- Integrated a neural conversational model in Facebook Messenger (PHP and Python) as an internal chatbot demo.
- Trained a neural model for question generation on 100k question/answer pairs as an additional module to the chatbot.
Computer Vision R&D Intern
- Developed and trained a compact CNN architecture (~3MB) with state-of-the-art performance for face recognition.
- I implemented on-device neural inference for Android (Java and Tensorflow).
- My work led to the submission and acceptance of a US patent (sole inventor) on compact neural models.
