Giovanni Dalmasso
Associate Professor
Barcelona, Catalonia, Spain
Summary
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Rockstar🎓
Top SchoolGiovanni Dalmasso is an associate professor and computational biologist with eight years of postdoctoral and research experience bridging mathematical modeling, systems biology, and scientific visualization. He has led and contributed to multidisciplinary projects from vascular and limb development to computational models of human moral decision-making, securing funding and mentoring the next generation of scientists. Technically fluent in Python and C++, he contributes to open-source tools like vedo—adding functionality and improving documentation for 3D scientific analysis—bringing data to life with publication-grade visualizations. Trained at Heidelberg and ETH Zürich with a PhD in Natural Sciences, he pairs rigorous theory with hands-on simulation and sci-art communication, often translating complex models into accessible narratives and educational outreach.
8 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy (PhD), Natural Sciences, cum laude, Doctor of Philosophy (PhD), Natural Sciences, cum laude at Heidelberg UniversityMaster Thesis, Computational Science & Engineering, Master Thesis, Computational Science & Engineering at ETH ZurichMaster of Science, Mathematical Engineering, 104/110, Master of Science, Mathematical Engineering, 104/110 at Politecnico di Torino
Italian, English, French, Spanish, German, Latin, Portuguese
Github Skills (7)
scientific-visualization10
vtk10
3d-graphics10
python10
numpy10
3d10
mesh9
Programming languages (1)
Github contributions (5)
marcomusy/vedo
Jan 2018 - Jun 2019
A python module for scientific analysis of 3D data based on VTK and Numpy
Role in this project:
Software Developer (focus on scientific visualization)
Software Developer (focus on scientific visualization)Contributions:12 commits, 17 pushes, 1 comment in 1 year 4 months
Contributions summary:Giovanni contributed to the `vedo` library by addressing code comments and descriptions to improve clarity. The user also added new functionality by implementing the `subDivideSurface` method. These changes focused on improving the documentation, usability, and functionality of the `vedo` library, a Python module for 3D data analysis.
pythonscientific-analysisscientific-visualizationvtkscientific-research
gioda/FeARLesS
Dec 2021 - Sep 2022
4D reconstruction of developmental trajectories using spherical harmonics
Contributions:1 release, 34 commits, 9 PRs in 9 months
heart-growthlimb-growthmorphogenesismouse-developmentnumpy
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