Magali Champion

Research Fellow, DM3L, University of Zurich | On leave from Université Paris Cité

Office Y27J16

Department of Mathematical Modeling and Machine Learning (DM3L)

University of Zurich

Winterthurerstrasse 190

CH-8057 Zurich, Switzerland

magali.champion[at]uzh[dot]ch

I am a Research Fellow in the Department of Mathematical Modeling and Machine Learning (DM3L) at the University of Zurich (UZH), working within Prof. Dr. Reinhard Furrer’s research group. I am currently on institutional leave from my position as an Assistant Professor in Statistics at IUT Paris-Rives de Seine, Université Paris Cité.

At UZH, I work closely on the ABN (Additive Bayesian Networks) project. I am also actively involved in academic development, assisting in the design and implementation of the new Bachelor of Science in Applied Mathematics and Machine Learning (AMML) as well as the upcoming Master’s program.

Broadly, my research focus lies in statistical machine learning for high-dimensional structures, graphical models and network inference, multi-omics data integration, and collaborative computational frameworks alongside clinical experts.

Previously, I spent a year as a Postdoctoral Researcher at the Stanford Center for Biomedical Informatics Research (BMIR). I completed my PhD in Applied Mathematics in December 2014 from Université Toulouse III under the supervision of Sébastien Gadat, Christine Cierco-Ayrolles and Matthieu Vignes.

For more info about me, please check my CV (last update 10/2023).

Responsabilities

Research interests

  • Statistical learning
    • high-dimensional data
    • graphical models
    • penalized linear regressions
    • sparse methods
    • clustering
    • statistical modeling
  • Computational biology
    • gene regulatory network inference
    • multi-omics data integration
    • applications to clinical and medical research

News

Apr 29, 2026 A new version of the l1 spectral-clustering paper is available online. đź“°
Feb 23, 2026 I am happy to share that I am officially back to work after a short, busy diaper-break. 🍼✨
Nov 14, 2025 Our new article, “All for One or One for All? A Comparative Study of Grouped Data in Mixed-Effects Additive Bayesian Networks”, has been published in Mathematics as part of the Special Issue Bayesian Networks: Parameter and Structure Learning with Their Real-World Applications for Decision Making. 📊

Selected publications

    1. Mathematics
      All for One or One for All? A Comparative Study of Grouped Data in Mixed-Effects Additive Bayesian Networks
      M. Champion, M. Delucchi, and R. Furrer
      Mathematics 2025