Alessandro Lucantonio
Associate Professor
Aarhus, Central Denmark Region, Denmark
Summary
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Senior🎓
Top SchoolAlessandro Lucantonio is an Associate Professor and head of the Computational Physics and Machine Learning Lab at Aarhus University, with a decade of research and academic leadership bridging theoretical mechanics, multiphysics simulation, and data-driven modeling. His career spans tenure-track and research roles at Scuola Superiore Sant'Anna and SISSA, grounded in a PhD on swelling-driven instabilities in soft materials and postdoctoral work blending functional analysis with applied mechanics. He develops computational methods—often finite-element and machine-learning hybrids—to tackle complex problems in soft condensed matter, biomechanics, and smart materials. Known for translating deep theoretical insight into practical simulation tools, he combines rigorous mathematical training with hands-on experimental collaborations dating back to work at Princeton. His background in aerospace and space engineering, graduated summa cum laude, gives him a unique multi-scale perspective from continuum mechanics to computational implementation.
10 years of coding experience
4 years of employment as a software developer
M.Sc. in Space Engineering, 110/110 cum laude, M.Sc. in Space Engineering, 110/110 cum laude at Università degli Studi di Roma 'La Sapienza'
Italian, English
Github Skills (66)
matrix10
statistics9
python9
gpu9
optimization9
pytorch9
autodiff9
machine-learning9
graph9
composable9
deap9
automatic-differentiation9
jit9
symbolic-regression8
julia8
Programming languages (6)
Github contributions (5)
alucantonio/Neutrino
Oct 2018 - May 2021
A fast and light library for GPU-based computation.
Contributions:36 pushes, 13 branches in 2 years 7 months
cudacomputationgpu-accelerationlightgpu
cpml-au/AlpineGP
May 2024 - Apr 2025
Symbolic regression of physical models via Genetic Programming.
Contributions:1 release, 5 PRs, 39 pushes in 10 months
genetic-programmingmodel-learningphysics-informed-machine-learningsymbolic-regression
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