Genentech: Matthieu Kirchmeyer | Machine Learning Scientist, Frontier Research, Prescient Design, Computational Sciences

Scientists / Our Scientists

I joined Genentech in June 2023 after completing a PhD in Machine Learning at Sorbonne Université (France). My PhD research focused on improving out-of-distribution generalization of deep learning models in the setting of classification and physical dynamics modeling. Prior to starting my PhD, I worked as a Machine Learning engineer on large-scale prediction models. I hold a Master’s degree in engineering from Mines-Paris and in Machine Learning from ENS Paris-Saclay.

Featured Publication

Diverse Weight Averaging for Out-of-Distribution Generalization.

NeurIPS 2022.

Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, patrick gallinari, Matthieu Cord.

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Generalizing to New Physical Systems via Context-Informed Dynamics Model.

ICML 2022.

Matthieu Kirchmeyer, Yuan Yin, Jeremie Dona, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari.

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My research focuses on developing machine learning models for Prescient Design’s molecular design framework, covering topics such as out-of-distribution generalization or physics-aware machine learning.

Sorbonne Université, PhD – 2023
ENS Paris-Saclay, MSc – 2017
Mines-Paris, MSc – 2017

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Matthieu Kirchmeyer

Machine Learning Scientist, Frontier Research, Prescient Design, Computational Sciences

Featured Publication

Diverse Weight Averaging for Out-of-Distribution Generalization.

Generalizing to New Physical Systems via Context-Informed Dynamics Model.