Dan Padilha is a Masters (Aerospace Engineering) student at The University of Tokyo and JAXA Institute of Space & Astronautical Science (ISAS). He has a background in computer science and 6 years of professional experience as a software systems and research engineer in quantum computing (at Rigetti in London), machine learning (at QxBranch in Adelaide), and embedded systems (at NICTA in Sydney). He has been involved in two successful start-up companies, presented at high-performance computing and emerging technologies conferences, run software workshops at over a dozen multinational corporations and universities, and led technical engagements designing novel algorithms and analytics platforms. He is currently a member of the Tsuda Laboratory at ISAS, working on software tools for astrodynamics research.
This talk briefly presents OrbitalTrajectories.jl, a library providing tools for the analysis of orbital trajectories for space mission design. Making use of the Julia scientific modeling ecosystem to easily define and extend high-fidelity simulations of spacecraft motion, we demonstrate how key techniques including meta-programming, symbolic computation, non-linear optimisation, and automatic differentiation work towards generating, analysing, and stabilising orbital trajectories.