I’m currently Ph.D student(2016-2020) at LORIA (a group of research CNRS, INRIA, University of Lorraine), working on Deep Learning & Natural Language Processing. My advisors are Christophe Cerisara and Claire Gardent (CNRS). During summer and winter 2017, I spent 6 months at Google Research Europe in Zurich, Switzerland, working on text-to-text generation and abstractive summarization. In spring 2018, I taught Machine Learning course for Master Sciences de la Cognition et Applications of University of Lorraine. I’m also member of DeepLoria working group.
Before starting my Ph.D, I graduated Master Stochastic Modeling (Data Science track) at University Paris 1 Pantheon Sorbonne and University of Paris Diderot, France. Prior to that, I followed a Master of Quantitative Economics & Finance at Ecole Polytechnique & HEC Paris. I’m originally from Vietnam, though I’ve also lived in these beautiful cities Paris, Nancy and Zurich.
Contact: hoa.le __at__ loria __dot__ fr
More in my CV
Participating in conference, events:
- EMNLP 2018
- International Workshop of Machine Learning & Artificial Intelligence at Telecom ParisTech
- Deep Learning & Reinforcement Learning Summer Schools 2018 (DLRL) at Vector Institute in Toronto (travel & registration fee grant)
- Seminar Artificial Intelligence of French-American Doctoral Exchange (FADEx 2018) (among 10 AI phd students represent France; travel, accommodation, food grant) [Poster]
- AAAI 2018
- Google Natural Language Processing Summit 2017 in Zurich
- Ecole Polytechnique – Paris Saclay Data Science Summer School 2017 [Recap VAE – GAN] [Poster]
- ICLR 2017
- NIPS 2016
- SIGDIAL 2017
- Google Research Europe Zurich (8/2017 – 2/2018) in Enrique Alfonseca‘s group. I worked mainly with Aliaksei Severyn and Daniele Pighin. This six months has been the most wonderful time I’ve had so far in my life.
- Teaching Memory and Machine Learning Course of Master Sciences de la Cognition et Applications (University of Lorraine, Master Erasmus Mundus) [Materials]
- Co-supervision internship of Master student Ecole de Mines Nancy. Topic ¨Abstractive Summarization with Variational Seq2seq¨
- Co-supervision internship of Master SCA Erasmus Mundus. Topic ¨Dialogue Act and Sentiment Analysis on Twitter using Memory Networks¨.
- “Multi-task dialog act and sentiment recognition on Mastodon”. Christophe Cerisara, Adedayo Oluokun, Somayeh Jafaritazehjani, Hoa T. Le. The International Conference on Computational Linguistics (COLING-18)
- “Do Convolutional Networks need to be Deep for Text Classification ?” Hoa T. Le, Christophe Cerisara, Alexandre Denis. Workshop on Affective Content Analysis of the AAAI-18 Conference on Artificial Intelligence, [Arxiv] [Poster] [Slides] [Code]
- Talk and research sharing at VietAI. Aug 2018.
- Organizing and maintaining Reading Group of Deep Learning & Natural Language Understanding in Synalp team. Feb-May 2018.
- A review of NIPS 2016 – DeepLoria. Jan 2017.
- Is Very Deep Convolutional Neural Network necessary for Text Classification? – Synalp. Nov 2016.
Fellowships & Achievements:
- Phd Fellowship of Lorraine Université d’Excellence (LUE). 2016.
- Master Fellowship to follow Statistics at Toulouse School of Economics by Agence Universitaire de la Francophonie (AUF) (renounce). 2013.
- Third Prize of National Olympic Programming Competition for Students (Vietnam). 2011.