Qiqi Wang is currently a visiting PhD student at the IfM, under the supervision of Professor Ajith Parlikad. Her research primarily focuses on battery health management and remaining useful life (RUL) prediction for complex systems. She has developed innovative prediction methods based on auto-feature extraction, CNNs, GPR, and diffusion models for battery lifetime and state-of-health predictions.

At the IfM, her current research involves empirical hierarchical models for industrial data and fast Bayesian updates.

Her work has been published in reputable journals, including Applied Energy, Journal of Energy Storage, Energy, and IEEE Transactions on Instrumentation and Measurement.

Qiqi Wang received her B.S. degree in Statistics from the University of Science and Technology of China, Hefei, China, in 2022. She is currently pursuing a Ph.D. in Systems Engineering at the City University of Hong Kong.