Biography

Hey there, I’m Victor, an applied ML researcher working in AI for science, currently at the Information and Network Dynamics Lab at the Ecole Polytechnique Fédérale de Lausanne (EPFL).

I develop methods for high-dimensional, spatio-temporal forecasting and inverse problems that remain robust under low signal-to-noise ratios and distribution shift, with application in biology and environmental sciences. I am particularly interested in hybrid modelling, integrating domain priors with deep learning and GPU-accelerated differentiable computing. I ship open-source libraries implementing these methods, lead funded research projects, and mentor students in applied machine learning and scientific computing.

Outside of work, I am a part-time alpinist, passionate about mountain adventures and writing. I also enjoy sailing and surfing occasionally. You can check out my alpine CV here.

Interests
Education
  • PhD in Environmental Sciences, 2023

    ETH Zürich, Switzerland

  • MSc in Energy and Environmental Sciences, 2018

    INSA Lyon, France

Open source software 🧑🏽‍💻

ML library

ML model

Domain-centric library

Posts

Publications

I also review for the Journal of Open Source Software, Ecology Letters, Ecography, Biodiversity and Conservation, and Methods in Ecology and Evolution.

Peer-reviewed

(2026). Chaotic Slow Slip Events in New Zealand from Two Coupled Slip Patches: A Proof of Concept. ARC Geophysical Research.

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(2025). Spatial biodiversity indicators and a composite index for conservation prioritization in Switzerland. bioRxiv.
Accepted in Ecology.

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(2025). A calibration framework to improve mechanistic forecasts with hybrid dynamic models. Methods in Ecology and Evolution.

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(2025). Differentiable Programming for Differential Equations: A Review. arXiv.
Accepted at SIAM Review.

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(2025). Species loss in key habitats accelerates regional food web disruption. Communications Biology.

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(2025). Temporal horizons in forecasting: a performance-learnability trade-off. Transactions on Machine Learning Research.

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(2024). A species-level multi-trophic metaweb for Switzerland. Scientific Data.

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(2023). Paleoenvironments shaped the exchange of terrestrial vertebrates across Wallace’s Line. Science.

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(2023). Ancient sedimentary DNA to forecast trajectories of ecosystem under climate change. Philosophical Transactions of the Royal Society B.

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(2022). Eco-evolutionary model on spatial graphs reveals how habitat structure affects phenotypic differentiation. Communications Biology.

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(2022). Deep learning approximations for non-local nonlinear PDEs with Neumann boundary conditions. Partial Differential Equations and Applications.

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Books

(2024). Accelerating renewable energy development while enhancing biodiversity protection in Switzerland. RE-BD AR2024.
Contributing author of chapters 2 and 5.

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(2022). Forward and inverse modelling of eco-evolutionary dynamics in ecological and economic systems.

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Conference papers

(2026). Biodiversity Profile Estimation with Earth Observation.
Accepted at the International Association for Pattern Recognition Workshop on Pattern Recognition in Remote Sensing 2026.

(2018). Episodic mineralising fluid injection through chemical shear zones. Australian Society of Exploration Geophysicists Extended Abstracts.

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Preprints

(2026). A Unified Framework for Prioritizing Habitat and Connectivity Conservation through Analytical Sensitivity. bioRxiv.
Revision requested from Landscape Ecology.

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(2026). Clustering biomes from space: from pixels to foundation models. SSRN.
Submitted to Remote Sensing of Environment.

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(2025). Multi-scale species richness estimation with deep learning. arXiv.
Revision requested from Nature Communications.

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(2023). Processes analogous to ecological interactions and dispersal shape the dynamics of economic activities. arRxiv.

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Selected funding

Teaching

Students

Current

Capucine Lechartre PhD co-supervision

A mechanistic approach to biome transitions across space and time

ETH Zurich, D-USYS · 2024-2028

Jeffrey Zweidler Master thesis

Forecasting invasive species range expansion using ecologically-informed neural networks

Department of Computer Science, ETH Zurich · 2025-2026

Co-supervision with Swiss Data Science Center

Moritz Dieing Master thesis

Attention-based deep multiple instance learning for species richness prediction

Department of Computer Science, ETH Zurich · 2025-2026

Co-supervision with Swiss Data Science Center

Alumni

Cecilia Valenzuela Agui Taste of research internship

Computational Biology and Bioinformatics, ETH Zurich · 2020

Nicolas Demolin Research internship

Applied Mathematics and Modeling, Polytech Nice · 2020

Teaching

2024

2023