Jukka Aho

Senior Scientist at VTT

Finland
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Summary

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Senior
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Top School
Jukka Aho is a Senior Scientist at VTT with 14 years of experience designing and optimising scientific algorithms for supercomputers and emerging quantum platforms. He builds scalable simulation frameworks—most notably OpenPFC, which he scaled to over 65,000 cores on LUMI with 8192^3 grids—bringing numerical physics and software engineering together for production-grade HPC workflows. His toolkit spans Julia, Python, C++, MPI and GPU programming, and he has hands-on experience running and benchmarking quantum algorithms like VQE and QAOA on real hardware. Jukka’s background in electrical, industrial and mechanical engineering gives him a pragmatic, systems-oriented approach that informs both architecture and algorithmic choices. He’s an active open-source advocate who balances academic rigor with delivery-focused engineering, having also prototyped real-time AI-backed voice assistants and industrial GPU-accelerated diagnostics as a consultant. Based in Finland, he prefers building shareable tools that let others reproduce and extend large-scale scientific computing results.
code14 years of coding experience
job7 years of employment as a software developer
bookBachelor's degree, Industrial Engineering, Bachelor's degree, Industrial Engineering at Lapland University of Applied Sciences
bookMaster's degree, Mechanical Engineering, excellent / ECTS A (4.64 / 5), Master's degree, Mechanical Engineering, excellent / ECTS A (4.64 / 5) at University of Oulu
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Github Skills (200)

cartesian10
programming-language10
parser10
gmsh10
co-simulation10
markdown10
depth-estimation10
computation10
pde10
integral10
scale10
html10
sketchup10
science10
abaqus10

Programming languages (16)

JavaC++CMakefileGoHTMLJupyter NotebookFortran

Github contributions (5)

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JuliaFEM/FEMBasis.jl

Jul 2017 - Mar 2021

FEMBasis contains interpolation routines for finite element function spaces. Given ansatz and coordinates of domain, shape functions are calculated symbolically in a very general way to get efficient code. Shape functions can also be given directly and in that case partial derivatives are calculated automatically.
Contributions:6 releases, 35 commits, 37 PRs in 3 years 8 months
partialagent-based-modelingnonlinearfenicssbml
JuliaFEM/FEMPlates.jl

Aug 2018 - May 2020

Plate bending formulations for JuliaFEM
Contributions:14 commits, 8 PRs, 7 pushes in 1 year 8 months
bendingplatejulia-languagejulia
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