MACHINE LEARNING GROUP

RPTU KAISERSLAUTERN-LANDAU

Muhammad Waasif Nadeem

Student assistant

Bio & Background

Waasif Nadeem works with the Machine Learning Group as a student assistant (Hiwi). He is currently pursuing a PhD in Mathematics at RPTU Kaiserslautern-Landau, focusing on mathematical methods for upscaling entropic learning. Before joining the group, he worked at Fraunhofer IWES as a student assistant, where he contributed to physics-informed modeling for wind farm planning.

Research interests

His research interests include Physics-Informed Neural Networks (PINNs), entropic learning, and rule-based learning approaches for solving physics-driven problems and differential equation–based systems.

Muhammad Waasif Nadeem portrait
Appointments and scientific matters
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Curriculum Vitae

Education

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

Professional Experience

2023 – 2025
Student assistant, Fraunhofer IWES, Germany
2021 – 2022
Data Scientist, Afiniti, Pakistan

Publications

  • 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.