Dan Padilha
Principal Software Engineer (Embedded Flight Software Lead) at Astroscale
Tokyo, Japan
Summary
👤
Senior🎓
Top SchoolDan Padilha is a Principal Software Engineer based in Tokyo with 15 years of professional experience leading embedded flight software for Astroscale’s next-generation space sustainability missions. He heads delivery of core GNC, RPO and CDH systems for flagship ADRAS-J2 and ISSA-J1 missions, blending hands-on avionics and real-time seL4 expertise with systems leadership. His background spans quantum computing research and commercialization at Rigetti, astrodynamics simulation at JAXA, and full-stack and ML/data analytics work, giving him a rare cross-domain fluency from kernel-level RTOS to cloud-scale simulation. An active open-source contributor, he has improved Julia’s ModelingToolkit.jl to better integrate externally registered functions and precompilation, reflecting deep attention to high-performance scientific tooling. Comfortable moving between research and delivery, he combines academic rigor (MEng, University of Tokyo) with proven product execution in both startups and national space agencies.
15 years of coding experience
10 years of employment as a software developer
BEng (Aerospace) & BSci (Computer Science), BEng (Aerospace) & BSci (Computer Science) at University of New South WalesAerospace Engineering (Exchange), Aerospace Engineering (Exchange) at University of MichiganUniversity of TokyoLake Tuggeranong College
English, Portuguese, Japanese
Github Skills (7)
differential-equations10
computer-algebra10
code-generation10
scientific-machine-learning10
julia10
computer-algebra-system10
testing9
Programming languages (10)
Github contributions (5)
SciML/ModelingToolkit.jl
Jun 2020 - Feb 2021
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:16 commits, 6 PRs, 15 comments in 8 months
Contributions summary:Dan significantly contributed to the ModelingToolkit.jl library by addressing issues related to function registration and code generation. They modified the `function_registration.jl` and `build_function.jl` files to enable the correct handling of externally registered functions and their integration into generated code. Additionally, they added test cases in `test/function_registration.jl` and modified `test/runtests.jl` to validate the implemented features and ensure proper functionality. The user's work centered on improving the integration of external functions within the ModelingToolkit framework, improving precompilation compatibility, and adding features related to evaluating symbolic expressions within the library.
sdescientific-machine-learningtransformationspartial-differential-equationsdifferential
dpad/basilisk
Feb 2024 - Nov 2024
Astrodynamics simulation framework
Contributions:184 pushes, 23 branches in 9 months
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.