MACHINE LEARNING GROUP

RPTU KAISERSLAUTERN-LANDAU

Muhammad Waasif Nadeem

PhD student

Bio & Background

Since 2026 Waasif Nadeem works with the Machine Learning Group as a PhD student supervised by Prof. Sophie Fellenz. Before joining the group, he worked at Fraunhofer IWES as a student assistant, where he contributed to physics-informed modeling for wind farm planning. He holds a master's degree in Industrial Mathematics from RPTU Kaiserslautern.

Research interests

His research interests include physics-informed machine learning, entropic learning, and transferable data generation approaches for physics-driven problems and dynamical systems.

Muhammad Waasif Nadeem portrait
Appointments and scientific matters
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Curriculum Vitae

Education

2023 – 2025
M.Sc. Industrial Mathematics, RPTU Kaiserslautern-Landau, Germany
2017 – 2021
BS Mathematics, Lahore University of Management Science, Pakistan

Professional Experience

Since 2026
PhD candidate - Researcher, RPTU Kaiserslautern, Germany
2025 – 2026
HiWi, ML Group, RPTU Kaiserslautern, Germany
2023 – 2025
Student assistant, Fraunhofer IWES, Germany
2021 – 2022
Data Scientist, Afiniti, Pakistan

Publications

  • Z. Lakdawala, W. Nadeem, and H. Kassem, "Predicting wind speeds in complex forested terrain using Reynolds-Averaged Navier-Stokes surrogates and data-driven feedforward convolutional neural networks," Energy and AI, 2026. https://doi.org/10.1016/j.egyai.2026.100738
  • K. Mumtaz, W. Nadeem, A. Khan, and Z. Lakdawala, “Investigating the use of physics informed neural networks for dam-break scenarios,” PLOS ONE, 2025. doi: 10.1371/journal.pone.0332694.
  • Z. Lakdawala, W. Nadeem, M. Doerenkaemper, and H. Kassem, "Investigating the usability of physics-informed machine learning approaches for wind farm planning," in Proc. 9th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2024), 2024.