I am a postdoctoral researcher at Aalto University, in the Probabilistic Machine Learning group, supervised by Samuel Kaski, Vikas Garg and Markus Heinonen. My work focuses on integrating human feedback into machine learning algorithms. We are specifically interested in applications involving Molecular Drug Design.
I successfully defended my PhD on February 18th, 2022. The manuscript can be found here and the slides here.
My thesis was conducted at Inria/Institut Curie, under supervision of François Fages and Annabelle Ballesta. We developed methods at the boundary of Systems Biology and Machine Learning to infer mechanistic models from time series data. A major contribution of the manuscript was to apply such methods to investigate the impact of systemic regulators (e.g. temperature, nutrient exposure, hormones) on the cellular circadian clock, in an attempt to personalize Cancer Chronotherapies.
Teaching:
Reviewing service:
PhD in Computer Science, 2022
Inria / Institut Curie / Ecole polytechique
Master's Degree 2nd year - Random modelling, Finance and Data Science, 2018
Université de Paris
Master's Degree 1st year - Applied Mathematics, 2017
Université de Paris