I'm a PhD student working in Graham Neubig's NeuLab in the Language Technologies Institute of Carnegie Mellon University. You can find my CV here and the list of my publications there. Currently (Spring 2021), I am pursuing an internship at Deepmind
My main area of interest revolves around developing machine learning models that can handle non-stationary data distributions, with a particular focus on natural language processing applications. Following this leitmotiv I have worked on distributional shift in the form of domain shift, adversarial perturbations and more recently continual learning of multiple tasks.
I also used to be an active contributor of DyNet, a toolkit for dynamic neural networks. Check it out!
Other than that I like reading sci-fi, sleeping, eating and playing video games. Recently I've picked up miniature painting and watercolor painting.
Before studying at CMU, I was an "Élève ingènieur" at École polytechnique in France.
My email is
pmichel1[at]cs.cmu.edu. You can also find me on Twitter, where I mostly tweet about my own work.
- I released the camera ready version of our paper Modeling the Second Player in Distributionally Robust Optimization. Code available on github.
- I gave a talk at the NLP with Friends online seminar on our ongoing work on parametric distributionally robust optimization. The talk was recorded and can be found on Youtube.
- New paper Weight Poisoning Attacks on Pre-trained Models accepted as a long paper at ACL 2020. The code is available on github.
Some projects I've been doing on the side (not so) recently: