About me
I am a research scientist at OpenAI, working on interpretability of language models, for AI safety. Before that, I was a postdoc at UC Berkeley in the Gallant Lab. I defended my Ph.D. in 2018, in the Image, Data, Signal department at Telecom ParisTech in France, supervised by Alexandre Gramfort and Yves Grenier. I graduated from Ecole polytechnique in 2013 and EPFL in 2015. More details can be found in my resume.
My work focuses on developing machine learning and signal processing methods, for interpreting human/animal brain recordings (electrocorticography, magnetoencephalography, functional magnetic resonance imaging, neuron spikes) and silicon brain recordings (large language model activations). I have also been a core developer of scikit-learn between 2015 and 2022.
News
- Aug 2023 - Joined OpenAI
- Sep. 2021 - Presented a tutorial at the conference on Cognitive Computational Neuroscience
- Jun. 2019 - Won PhD thesis award - 1st prize in Signal, Image and Vision, from the Club EEA, GRETSI and GdR ISIS
- Feb. 2019 - Joined the Gallant Lab at UC Berkeley as a post-doc
- Nov. 2018 - Won PhD students award - 1st prize at Université Paris-Saclay STIC doctoral school
- Nov. 2018 - Defended my PhD - Non-linear models for neurophysiological time series
Blog posts
- March 2018 - Dask-Distributed and Joblib
Publications
2023
2022
2018
PhD student award - 1st prize at Université Paris-Saclay STIC doctoral school [link]
PhD thesis award - 1st prize in Signal, Image and Vision, from the Club EEA, GRETSI and GdR ISIS [link] [news]