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.
I am currently a research intern at Google, developing new methods in Reinforcement Learning from Human Feedback (RLHF) to improve LLM model quality within the Gemini team. I was already a student researcher within this team in 2023.
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.
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
[July 26, 2024] I am co-organising a workshop on RL theory & practice at ICML 2024.
[June 3, 2024] I am back at Google as a Research Intern, working on RLHF and reward modelling for Gemini.
[Jan 22, 2024] My paper on synthetic preference generation, based on work during my internship at Google, is out on arXiv.
[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.
See my Google Scholar profile for a full list of publications.