Hi! I’m Alizée, a PhD student in Machine Learning and a fellow at the ETH AI Center in Zürich. I am lucky to work with Prof. Gunnar Rätsch and Prof. Bernhard Schölkopf. I am also part of the ELLIS PhD program. My main research goal is to develop ML solutions for decision support and treatment recommendation systems, with an interest for offline reinforcement learning, representation learning and causal inference.
In 2023, I was a student researcher at Google, developing new methods in Reinforcement Learning from Human Feedback (RLHF) with Aliaksei Severyn and the wider Bard team.
Before my PhD, I led a project on imitation learning for clinical decision-making with Prof. Mihaela van der Schaar at the University of Cambridge. My professional experience also includes medical device development and software engineering at CERN. I studied Physics, Materials Science and Machine Learning at Cambridge, where I consistently ranked first in my year.
I am actively looking for excellent Masters' students to supervise for their thesis (preferably at ETH). Reach out if our interests overlap!
PhD in Machine Learning, started 2021
ETH Zürich
MPhil in Machine Learning and Machine Intelligence, 2021
University of Cambridge
BA MSci in Materials Science, 2020
University of Cambridge
[Jan 16, 2024] My paper on Delphic Offline RL is accepted to ICLR 2024.
[Dec 10, 2023] My paper on Embeddings for Clinical Time-Series is accepted to ML4H 2023.
[July 28, 2023] I presented my paper on Delphic Offline RL at 3 ICML workshops and at EWRL (including an oral!).
[May 30, 2023] I will be spending six months as a Student Researcher at Google Zürich, working with Aliaksei Severyn on RL methods to improve LLM training. Super excited!
[April 24, 2023] My paper on Temporal Label Smoothing is accepted to ICML 2023. See you in Hawaii 🌺🏝
See my Google Scholar profile for a full list of publications.