Fredrik Carlson
Team Lead, Control-systems at FKBC AB
Lund, Skåne County, Sweden
Summary
🤩
Rockstar🎓
Top SchoolFredrik Carlson is a control-systems team lead and researcher with 10 years' experience applying machine learning, system identification and signal processing to robotics and scientific computing. Based in Lund, Sweden, he leads control-systems work at JuliaHub while contributing significant back-end and optimizer improvements to prominent open-source ML projects such as Flux.jl and ModelingToolkit.jl. His background spans academia (PhD and postdoc in automatic control) and industry R&D, with hands-on experience implementing shape inference, Jacobian tooling and discrete-system features that bridge symbolic and numerical workflows. Known for pragmatic engineering of core libraries, he combines theoretical depth in control with practical expertise shipping robust algorithms for real-world robot and modeling applications.
10 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Automatic control, Doctor of Philosophy - PhD, Automatic control at Lund UniversityTech. Lic., Automatic Control, NA, Tech. Lic., Automatic Control, NA at Lunds universitet
Stackoverflow
1,351reputation
176kreached
29answers
4questions
julia
top-5%
Github Skills (41)
symbolic-computation10
symbolic-computing10
ode10
artificial-neural-networks10
optimizers10
mathematics10
machine-learning10
optimizer10
inference10
math10
differential-equations10
deeplearning-ai10
deep-learning10
tensorflow10
flux10
Programming languages (15)
Github contributions (5)
SciML/ModelingToolkit.jl
Oct 2021 - Jan 2023
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Role in this project:
Back-end Developer
Back-end DeveloperContributions:94 reviews, 103 commits, 115 PRs in 1 year 3 months
Contributions summary:Fredrik made several contributions to the `modelingtoolkit.jl` repository. These included implementing features for discrete systems, adding tests for symbols in discrete solutions, and fixing docstrings. They also worked on including root-finding equations in `ODESystem` and added documentation of the internals. The user's work primarily focused on expanding and improving the functionality of the modeling framework.
sdescientific-machine-learningtransformationspartial-differential-equationsdifferential
JuliaSymbolics/Symbolics.jl
Nov 2021 - Nov 2022
Symbolic programming for the next generation of numerical software
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 reviews, 20 commits, 25 PRs in 1 year
Contributions summary:Fredrik contributed to the `symbolics.jl` repository, focusing on enhancing the symbolic computation capabilities. They implemented and refined functionalities related to difference operations, including defining the `^` operator and improving the `Difference` type. Their work also involved adding and modifying methods for array operations and Jacobian calculations, addressing bugs related to array variable handling and improving code related to documentation.
symbolic-computationsymbolic-computingcomputer-algebra-systemmathematicssql
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