M. (Meiling) Cheng


I am a Postdoc researcher in the Geoscience & Remote Sensing Group. Previously, I obtained my PhD degree in Imperial College London in 2022. Prior to joining Imperial College, I obtained master's and bachelor’s degrees in Wuhan University in China. 


My research interests and expertise revolve around developing novel machine learning technologies addressing a wide range of issues across computational fluid dynamics, hydrology, and climate. In my current project, my work will focus on data-driven atmospheric cloud research supervised by Franziska Glassmeier. I will combine machine learning methods with partial physical knowledge such as conservation laws to efficiently and accurately describe cloud characteristics and processes across different data sources.

(Key) publications

  • Cheng, M., Fang, F., Pain, C.C. and Navon, I.M., 2020. Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network. Computer Methods in Applied Mechanics and Engineering, 365, p.113000.
  • Cheng, M., Fang, F., Navon, I.M., Zheng, J., Tang, X., Zhu, J. and Pain, C., 2022. Spatio‐Temporal Hourly and Daily Ozone Forecasting in China Using a Hybrid Machine Learning Model: Autoencoder and Generative Adversarial Networks. Journal of Advances in Modeling Earth Systems, 14(3), p.e2021MS002806.


More publications click Researchgate.net

Meiling Cheng

Postdoctoral researcher

  • + 31 610417969
  • m.cheng-1@tudelft.nl
  • Faculty of Civil Engineering and Geosciences

    Building 23, room 2.09

    Stevinweg 1 / PO box 5048

    2628 CN Delft / 2600 GA Delft

    Mon - Fri