Joris Gillis
Feelancing Scientific Computing Expert at KU Leuven
Leuven, Flemish Brabant, Belgium
Summary
🤩
Rockstar🎓
Top SchoolJoris Gillis is a mechanical engineer turned scientific computing specialist with 15 years of experience combining advanced control theory and hands-on software development. As co-developer of the widely used CasADi library and contributor to acados, he designs and implements numerical optimization and code-generation features that bridge research-grade algorithms and practical, high-performance solvers. Based in Leuven, he splits his time between a KU Leuven post-doc role in advanced robotics and freelance consulting through Yacoda, rapidly prototyping and accelerating CasADi-based applications for industry and academia. Known for composing tools and ideas into working prototypes quickly, he has a knack for turning complex stability and optimal-control research into reliable, production-ready components. A persistent collaborator, he admits to sometimes getting carried away helping others—evidence of his drive to make impactful, usable scientific software.
15 years of coding experience
6 years of employment as a software developer
Bachelor of Applied Science (B.A.Sc.), Mechanical Engineering, summa cum laude, Bachelor of Applied Science (B.A.Sc.), Mechanical Engineering, summa cum laude at KU LeuvenASO - Latin-Math, 87 %, ASO - Latin-Math, 87 % at Sint-Gummarus CollegeMaster's degree, Mechanical Engineering, magna cum laude, Master's degree, Mechanical Engineering, magna cum laude at Katholieke Universiteit Leuven
English, French, Dutch, Spanish, German
Github Skills (12)
numerical-optimization10
automatic-differentiation10
code-generation10
c-language10
cprogramming-language10
casadi10
python10
linear-algebra10
optimization10
testing9
embedded8
cmake7
Programming languages (18)
Github contributions (5)
casadi/casadi
Dec 2010 - Jan 2023
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript
Role in this project:
Back-end Developer & Algorithm Implementer
Back-end Developer & Algorithm ImplementerContributions:67 releases, 5 reviews, 5017 commits in 12 years 3 months
Contributions summary:Joris appears to be primarily focused on enhancing the CasADi library, a framework for symbolic and numerical optimization, especially concerning the mathematical aspects of the library. The commits involve implementing functions, addressing issues, and refactoring existing code. They are also seen working on unit tests and incorporating new features, as evidenced by the inclusion of code generation and integration functionalities.
automatic-differentiationcasadicode-generationcppipopt
acados/acados
Jun 2020 - Dec 2020
Fast and embedded solvers for nonlinear optimal control and nonlinear model predictive control
Role in this project:Backend Developer
Backend DeveloperContributions:1 review, 10 commits, 13 PRs in 5 months
Contributions summary:Joris primarily focused on improving the Python-based interfaces and code generation aspects of the acados library. They addressed confusion in the CasADi interfaces, updated external cost implementations, and fixed bugs related to matrix handling and data passing within the solvers. The user also refactored and optimized existing code and made contributions related to C code generation.
nonlinear-model-predictive-controlembeddedoptimizationnonlinearoptimal
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.