Mathilde Chen

Postdoctoral fellow. Supervision: David MAKOWSKI (UMR MIA, & Nicolas GUILPART (UMR Agronomie).


Current project

Using historical data and future climate projections, we will study the effect of climate change on the productivity of soybean and maize in Europe using meta-analysis and machine learning methods. Then, we will evaluate with optimization methods how the maize-soybean association (growing the two crops together in the same field in the same year) could help Europe to become self-sufficient in proteins without increasing its cultivated area in a context of climate change.



  • Chen, M., Schievano, A., Bosco, S., Evidence map of the benefits of enhanced-efficiency fertilisers for the environment, nutrient use efficiency, soil fertility, and crop production. (2023). Evidence Research Letters. 10.1088/1748-9326/acb833
  • Chen, M., Landré, B., van Hees, V.T., van Gennip, A.C., Bloomberg, M., Yerramalla, Y.S., Benadjaoud, M.A., Sabia, S. Identification of physical activity and sedentary behaviour dimensions that shape mortality risk in older adults: a machine learning approach. eClinical Medicine, 55: 101773 (2023). 10.1016/j.eclinm.2022.101773
  • Chen, M., Yerramalla, Y.S., van Hees, V.T., Bloomberg, M., Landré, B., Fayosse, A., Benadjaoud, M.A., Sabia, S. Individual barriers to an active lifestyle at older ages among Whitehall II study participants after 20 years of follow-up. JAMA Network Open, 5(4):e226379. https://doi:10.1001/jamanetworkopen.2022.6379
  • Machado-Fragua, M.D., Landré, B., Chen, M., Fayosse, A., Dugravot, A., Kivimaki, M., Sabia, S., Singh-Manoux, A., Circulating serum metabolites as predictors of dementia: a machine learning approach in a 21-year follow-up of the Whitehall II cohort study [in review].
  • Makowski, D., Bosco, S., Chen, M., Montero-Castaño, A., Pérez-Soba, M., Schievano, A., & Terres, J. Systematic review of meta-analyses to assess the impacts of farming practices - A methodological framework. (2021). [preprint]
  • Chen, M., Brun, F., Raynal, M., Makowski, D. Forecasting severe grape downy mildew attacks using machine learning. PLOS ONE 15(3): e0230254 (2020).
  • Chen, M., Brun, F., Raynal, M., Makowski, D. Delaying the first grapevine fungicide application reduces exposure on operators by half. Sci Rep 10, 6404 (2020).
  • Chen, M., Brun, F., Raynal, M., Makowski, D. Timing of grape downy mildew onset in Bordeaux vineyards. Phytopathology 109(5) (2019). 10.1094/PHYTO-12-17-0412-R