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Xiaoxi Jia received her M.Sc. degree in mathematics (optimization) from Nanjing Normal University in China in 2020, her master thesis was about the algorithm design for quasi-variational inequalities and generalised Nash equilibrium problems. She then obtained the Ph.D. degree in Optimization in 2023, from University of Wuerzburg in Germany, under the supervision of Christian Kanzow. Her Ph.D. thesis focused on the analysis of the (safeguarded) augmented Lagrangian methods and the corresponding subproblem solvers for solving a series of structured optimization problems. She is now a postdoctoral researcher in the Mathematical Optimization for Data Science group of Peter Ochs, and focusing on quasi-Newton methods for nonconvex and nonsmooth optimization problems.