JuliaCon 2023

Jieqiu Shao

Jieqiu Shao (Jay) is a pursuing a PhD in Electrical Engineering at the University of Colorado at Boulder under Dr. Marco Nicotra's supervision. Jay completed his MS in Mechanical Engineering at the University of Colorado at Boulder in 2020. He earned his Bachelor of Science in Mechanical Engineering from the University of Iowa in 2018.

Jay's MS thesis, which now continues as his PhD project, focuses on the Control of Optical Atomic Lattices for Quantum Inertial Sensing. Along the way, Jay was the primary catalyst for Q-PRONTO, which is an extremely successful byproduct of a class project he worked on with Prof. John Hauser and has, since then, flourished beyond expectations.


Session

07-27
12:00
30min
PRONTO.jl: Trajectory Optimization in Function Space
Mantas Naris, Jieqiu Shao

PRONTO.jl is a Julia implementation of the Projection-Operator-Based Newton’s Method for Trajectory Optimization (PRONTO). PRONTO is a direct method for trajectory optimization which solves the optimal control problem directly in infinite-dimensional function space. It is capable of achieving quadratic convergence and has potential applications ranging from aerospace to quantum sensing.

JuliaCon
32-124