Roxie (Ruoxi) Jiang

Roxie is a Computer Science PhD student at the University of Chicago advised by Professor Rebecca Willett. Previously, she received her master’s degree in Operations Research at Columbia University and bachelor’s degree at Xi’an JiaoTong University.

Roxie’s research interests lie in machine learning for dynamical systems and its applications in scientific computing. In particular, she works on learning structural hidden representations of the high-dimensional data. Her work has been applied to addressing inverse problems with uncertainty quantification and designing practical algorithms to achieve data efficiency in decision-making problems (i.e., bandits). Currently, she is interested in predicting high-dimensional chaotic systems with deep learning.