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Keivan Kaveh

Technische Universität München

Lehrstuhl für Wasserbau und Wasserwirtschaft (Prof. Rutschmann)


Arcisstr. 21
80333 München

Higher Education

  • Doctoral Candidate, Chair of hydraulic and water resources engineering, TU Munich, since 2013
  • M.Sc. Hydraulic structures, Semnan University, Iran, 2011
  • B.Sc. Civil engineering, University of Mazandaran, Iran, 2008

Professional Experiences

  • Project VieWBay: Coupling and of hydrology and hydromorphodynamics in large scales - an approach for whole Bavaria.
  • Teaching Assistant for the Environmental Hydrodynamic Modelling course and Flow-3D software
  • Teaching Assistant for the River Engineering and Hydro-Morphology course and HEC-RAS software


Journal papers

1. Kaveh, K., Bui, M. D., & Rutschmann, P. (2017). A comparative study of three different learning algorithms applied to ANFIS for predicting daily suspended sediment concentration. International Journal of Sediment Research, 32(3), 340-350.

2. Bui, M. D., Kaveh, K., & Rutschmann, P. (2017), Performance analysis of different model architectures utilized in an adaptive neuro fuzzy inference system for contraction scour prediction, Journal of Mechanical and Civil engineering, IOSR.

3. Bui, M. D., Kaveh, K., Penz, P., & Rutschmann, P. (2015). Contraction scour estimation using data-driven methods. Journal of Applied Water Engineering and Research, 3(2), 143-156.

4. Kaveh, K., Bui, M. D., & Rutschmann, P. (2015). Improvement of ANFIS model by developing of novel hybrid learning algorithms for contraction scour modeling. Mathematics in Engineering, Science & Aerospace (MESA), 6(4).

5. Hosseinjanzadeh, H., Hosseini, K., Kaveh, K., & Mousavi, S. F. (2015). New proposed method for prediction of reservoir sedimentation distribution. International Journal of Sediment Research, 30(3), 235-240.

6. Kaveh, K., Hosseinjanzadeh, H., & Hosseini, K. (2013). A new equation for calculation of reservoir’s area-capacity curves. KSCE Journal of Civil Engineering, 17(5), 1149-1156.


1. Kaveh, K., Bui, M.D., & Rutschmann, P. (2018), Integration of Artificial Neural Networks into TELEMAC-MASCARET system for hydro-morphodynamic modelling, Wasserbau-symposium, 2018, TU Graz, Austria.

2. Kaveh, K., Bui, M.D., & Rutschmann, P. (2018), Development of an Artificial-Neural-Network-based concept for hydro-morphodynamic modelling in rivers, The 5th IAHR Europe Congress, 2018,Trento, Italy.

3. Bui, M. D.; Kaveh, K.; Ateeq-Ur-Rehman, S.; Rutschmann, P. (2017), Artificial neural networks for modelling sediment transport in rivers. In Proceedings of the 20th Vietnam Conference on Fluid Mechanics, Can-Tho, Vietnam; p 15.

4. Kaveh, K., Bui, M. D., & Rutschmann, P. (2016). A new approach for morphodynamic modeling using integrating ensembles of artificial neural networks. In „Wasserbau–mehr als Bauen im Wasser “. Beiträge zum 18. Gemeinschafts-Symposium der Wasserbau-Institute TU München, TU Graz und ETH Zürich (pp. 304-315).

5. Bui, M. D., Huber, D., Kaveh, K., Da Silva, A. M. F., & Rutschmann, P. (2016). Application of artificial neural networks for river regime. River Flow 2016: Iowa City, USA, July 11-14, 2016, 154.

6. Kaveh, K., Bui, M. D., & Rutschmann, P. (2015). New hybrid learning algorithms in adaptive neuro fuzzy inference systems for contraction scour modeling. In Proc. of the 14th International Conference on Environmental Science and Technology Rhodes, Greece.

7. Bui, M.D.; Kaveh, K. & Rutschmann, P. (2015), Integrating artificial neural networks into hydromorphological model for fluvial channels, The 36th IAHR World Congress, 2015, The Hague, the Netherlands.

Research Interest

  • Data-driven methods
  • Fluid mechanics
  • Hydro-morphodynamic modelling
  • Erosion and sedimentation