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I am a mathematician and computational scientist interested in how mathematical models, simulation, data and computation can help us understand complex systems.
My research crosses traditional disciplinary boundaries: from applied mathematics and molecular simulation to computational biology, artificial intelligence, scientific computing, human decision-making and questions at the intersection of AI, ethics and society.
Rather than being tied to a single application domain, I am especially interested in methods and ideas that transfer across scales and disciplines.
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Differential equations |
Numerical simulation |
Molecular dynamics |
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Systems biology |
Machine learning |
Moral decision-making |
Environmental and ecological systems also appear as application domains within this broader computational and mathematical framework.
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An open university mathematics project combining rigorous theory, extensive problem collections and computational resources.
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4D reconstruction and analysis of developmental trajectories using spherical harmonics, connecting mathematical representations, scientific computing and biological morphogenesis.
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Research at the intersection of stochastic modelling, numerical mathematics and computational simulation.
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🌿 ◈ vedoOpen-source Python library for scientific analysis and visualization of 3D objects and data. I am a contributor to the project and use it extensively across my own scientific work.
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Not all of my research lives on GitHub.
My broader work includes molecular dynamics and biomolecular modelling, multiscale biological systems, machine learning, scientific visualization, mathematical and stochastic modelling, human moral decision-making, and the societal and educational implications of artificial intelligence.
I am particularly drawn to problems where a method developed in one field unexpectedly becomes useful in another.
I believe scientific and educational work becomes more valuable when it can be inspected, reproduced, reused and improved.
Alongside research, I develop open educational resources, computational teaching material and reproducible scientific workflows. Where possible, public projects include documented source material, explicit licensing, archival releases and persistent citations.
Research · Teaching · Open Science
Barcelona