Ming Qiu is a first-year PhD student whose current research focuses on stochastic optimal control and numerical methods. Her interests include the study of Markov chain approximation-based deep learning algorithm and its applications in insurance strategies.
Prior to the Centre of Actuarial Studies, she received a B.Sc. (Hons) from the University of Sydney (2016) and an M.A. from UC Berkeley (2018). She has previously worked as a data engineer at OneConnect in Shanghai.