Inhaltspezifische Aktionen

Qing Lin

Contact

+49 641 99 12710

+49 641 99 12709

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Professional Experience and Teaching
Since 02/2022   ZEU Research Associate
08/2017 - 07/2020  

Research assistant, TU München, Lehrstuhl Hydrologie und Flussgebietsmanagement

Projekt: Hinweiskarte Oberflächenabfluss und Sturzflut unter Bayerischen Landesamtes für Umwelt
www.hios-projekt.de

  

Education
Since 08/2017    PhD in hydrology, Ingenieurfakultät Bau Geo Umwelt, TU München, Germany,
(Thesis submitted)
10/2013 - 09/2016   MSc in Computational Mechanics, Ingenieurfakultät Bau Geo Umwelt, TU München, Germany
09/2009 - 07/2013   BSc. Theoretical and Applied Mechanics, Department of Aeronautics and Astronautics, 
Fudan Universität, Shanghai, China

 

Further Information
Affiliation          Research Associate
Focus Area    
References               
Fields of Interest  
  • Machine Learning Models
  • Flood Forecasting
  • Climate Modelling
Project involvement
Publications   

Peer-review Articles

  • Multistep flood inundation forecasts with resilient backpropagation neural networks: Kulmbach Case Study Lin et al., Water, 12(12), 2020, 3268. https://doi.org/10.3390/w12123568
  • Prediction of maximum flood inundation extents with resilient backpropagation neural network: Case Study of Kulmbach Lin et al., Frontiers in Earth Science, Vol. 8, 2020, p332. http://www.doi.org/10.3389/feart.2020.00332
  • Inclusion of narrow flow paths between buildings in coarser grids for urban flood modeling: virtual surface links
    Ramsauer et al., Water, 2021, 13(19), 2629 https://www.doi.org/10.3390/w13192629
  • Optimization of Artificial Neural Network (ANN) for Maximum Flood Inundation Forecasts
    Zhu et al., Water, 13(16), 2021, 2252 http://www.doi.org/10.3390/w13162252

 

Conference Papers on hydrodynamic modelling

 

Conference Papers on parallel-computing