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Mathieu Ravaut


I am a 3rd-year PhD student in computer science at Nanyang Technological University (NTU) School of Computer Science and Engineering (SCSE) in Singapore. I work in NTU-NLP lab under the supervision of Dr. Shafiq Joty. My research is funded by a SINGA scholarship, and I am attached to ASTAR Institute for Infocomm Research (I2R) where I am supervised by Dr. Nancy Chen.

My research interest is currently in natural language processing (NLP), after extensive experience in machine learning for healthcare. Within NLP, I am doing my PhD in abstractive text summarization. Specifically, I am interested in several aspects of summarization: second-stage methods which learn summarization at the entire sequence-level rather than at the token level, unsupervised and few-shot summarization, and controllable summarization.

Prior to NTU, I worked as a Machine Learning Research Scientist at Layer 6 AI, TD Bank's AI lab in Toronto. At Layer 6, I worked on applied research projects in machine learning for healthcare in collaboration with ICES, and NLP. My research at Layer 6 has been featured in Nature and JAMA.

I hold a Master of Science in Applied Computing (MScAC) from the University of Toronto with a concentration in Data Science. Before UofT, I studied Engineering (specialized in applied mathematics) at Ecole Centrale Paris, a French Engineering School which is now known as CentraleSupelec and part of the newly created Universite Paris-Saclay. During my Engineering studies I interned at Thales and in ASTAR I2R's Visual Computing Lab in Singapore. Previously, I studied classe preparatoire (a very French thing) in mathematics and physics at Lycee Montaigne in Bordeaux.

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Random facts about me:
  • I've lived in 10 cities across 7 countries. Singapore is my favorite city so far.
  • I mostly wear black t-shirts.
  • Like a lot of people, I started machine learning with Andrew Ng's course back in 2016. Since then, I completed more than 10 MOOCs, and I strongly advocate for online education.
  • I love NLP since I discovered word2vec in 2017.