Alfredo Bici
PHD Student at KTH Royal Institute of Technology
Stockholm, Sweden
Summary
👤
Senior🎓
Top SchoolAlfredo Bici is a PhD student at KTH Royal Institute of Technology specializing in lightweight, multifunctional composite materials with a focus on leveraging the electrochemical properties of carbon fibers. With a 9-year technical background rooted in aerospace engineering and top honors from Politecnico di Torino, he blends rigorous academic research with practical simulation and development experience, including modeling rotary-wing drones in Matlab/Simulink. Alfredo is also an active contributor to high-profile open-source projects like the Julia programming language, where he has improved sparse matrix performance and fixed core bugs—an unusual cross-disciplinary skillset that bridges computational performance engineering and materials science. Based in Stockholm, he brings a systems-level perspective to problems, combining hands-on coding, simulation, and materials characterization to push toward truly multifunctional structures.
9 years of coding experience
High School Diploma, IT and Telecommunications, 100/100 Cum Laude, High School Diploma, IT and Telecommunications, 100/100 Cum Laude at ITIS G. GalileiKTH Royal Institute of TechnologyBachelor's degree, Aerospace Engineering, 110/110 Cum Laude, Bachelor's degree, Aerospace Engineering, 110/110 Cum Laude at Politecnico di Torino
English, Italian, Albanian
Github Skills (10)
sparse-matrix10
performance-optimization10
linear-algebra10
julia10
numerical-computing9
algorithm9
algorithms9
hpc8
programming-language8
scientific-computing8
Programming languages (4)
Github contributions (5)
JuliaLang/julia
Dec 2018 - Apr 2021
The Julia Programming Language
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:3 reviews, 16 commits, 19 PRs in 2 years 4 months
Contributions summary:Alfredo's contributions primarily focused on optimizing the performance of sparse matrix operations within the Julia programming language. This involved implementing and improving the `circshift!` function for `SparseMatrixCSC` and `SparseVector` types. The user also made significant improvements to the `sprand` function for generating sparse matrices, leading to faster execution times and improved code clarity. Furthermore, the user implemented copy functions and corrected several bugs in the codebase.
sciencejulia-languagemachine-learningjulialangpetsc
abraunst/StringFigures.jl
Mar 2024 - Oct 2024
Contributions:15 PRs, 93 pushes, 6 branches in 7 months
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