Digital twins for biology
Personalised and system-specific computational models that integrate mechanisms, measurements and uncertainty.
- Gut Digital Twin
- Eye2Heart
- FermenTwin
Research scientist · Applied mathematics
Mathematical modelling and learning for biological digital twins.
I develop mechanistic and data-informed mathematical models for complex biological systems. My research combines digital twins with inverse problems, reduced-order modelling and physics-informed neural networks to integrate experimental data, uncover hidden dynamics and deliver efficient predictions.
INRAE · MaIAGE unit · Dynenvie team · Jouy-en-JosasInria · MUSCA team · Saclay Île-de-France
Research focus
Two connected themes
I combine mechanistic biological modelling with computational methods that learn from data while retaining mathematical structure.
Learning and reducing models
Efficient, data-informed models for inference and prediction, bringing together inverse problems, model reduction and physics-informed neural networks.
Explore this themeSupervision
Supervision
Doctoral, postdoctoral and internship projects across mathematical biology, microbial communities, digital twins and physics-informed learning.
Ongoing PhD and postdoctoral supervision
- X. Amorós Gabarrón · PhD, 2026–presentModelling plant immune-response dynamics with physics-assisted artificial intelligence.Co-supervised with S. Bottini, Institut Sophia Agrobiotech, Sophia Antipolis; R. Duvigneau, Inria Sophia Antipolis; and A. Garcia-Molina, Centre for Research in Agricultural Genomics, Barcelona.
- G. Lacour · Postdoctoral researcher, 2025–2026Physics-informed modelling and data integration for microbial community dynamics — CULTISSIMO project.Co-supervised with B. Laroche, INRAE Jouy-en-Josas.
Completed PhD supervision
- E. Pastremoli · PhD, 2023–2026Towards a digital twin of the gut microbiota: composition, function and interactions with the host.Co-supervised with B. Laroche, INRAE Jouy-en-Josas.
- J. Kowalski · PhD, 2022–2026Whole-body vascular transport and pharmacokinetic models, with applications to imaging and the liver.Co-supervised with I. Vignon-Clementel, Inria Saclay Île-de-France.
- M. Haghebaert · PhD co-supervision, 2023Dynamic modelling of complex microbial ecosystems from experimental time-series observations.Third-year co-supervision with B. Laroche, INRAE Jouy-en-Josas.
- CEMRACS project · 2023L. Perrin, T. Saigre and P. J. Hossie — estimation of microbial-community interactions using a neural-network-based generalized smoothing algorithm.
Student internships
2026A. Pelella, M. Baggi and B. Allioux — INRAE Jouy-en-Josas
V. Cagnazzi — Université Paris Cité
V. Cagnazzi — Université Paris Cité
2025V. Schmitt, M. Denoual and O. Gawas — INRAE Jouy-en-Josas
2024F. Hughes — University of Maine
A. Dechamps and Y. Jouanaud — INRAE Jouy-en-Josas
K. Hezez — Sorbonne Université
A. Dechamps and Y. Jouanaud — INRAE Jouy-en-Josas
K. Hezez — Sorbonne Université
2023K. Lyons — Université Paris Cité
2022J. Kowalski — Inria
2021L. Thiebaud — Inria
2020A. Walczak; G. Kim, J. Liu, Z. Sun and B. Xiao — Imperial College London
Join the research
Job and student opportunities
Prospective interns, doctoral candidates, postdoctoral researchers and collaborators interested in mathematical biology, digital twins, inverse problems or scientific machine learning are welcome to get in touch.
Open positions will be listed here when available. Spontaneous enquiries should include a short description of your interests and relevant experience.