Muhammad Ahsan, PhD, Engr.

Researcher in Advancing Structural Health Monitoring and Intelligent Fault Diagnosis
Politechnika
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Short Biography

Dr. Muhammad Ahsan received his Bachelor’s degree in Electrical Engineering from Air University, Islamabad, Pakistan, in 2014, and his Master's degree in Control Theory and Control Engineering from Nanjing University of Science and Technology, Nanjing, China, in 2020. He completed his Ph.D. in July 2025 from Silesian University of Technology, Gliwice, Poland, where he conducted multidisciplinary research bridging signal processing, machine learning, and control engineering. Dr. Ahsan has authored over 20 publications in reputed journals and conferences, contributing to the advancement of fault diagnosis in bearings, machine health monitoring, and control system design. The aim of Dr. Ahsan's research is to enhance the reliability, safety, and efficiency of industrial systems, with a particular emphasis on optimization, nonlinear control, and robust multidisciplinary approaches. Through his work, Dr. Ahsan continues to push the boundaries of knowledge, making significant contributions to both academia and industry.

Research Interests

I'm mainly interested in the Vibration Analysis and Health Monitoring; Signal Processing and Machine Learning; Nonlinear and Distributed Control.

News & Announcements

  • [July, 2025]: I successfully defended my doctoral dissertation and granted Doctoral title in the field: Engineering and Technical Sciences and discipline: Automation, Electronics, Electrical Engineering and Space Technologies.
  • [July, 2025]: I will defend my doctoral dissertation on "Vehicle diagnostic using artificial intelligence and digital signal processing methods" on July 9th 2025 at Faculty of Automatic Control, Electronics and Informatics, ul. Akademickie j 16 w Gliwicach.
  • [July, 2025]: Our paper, Enhanced LeNet-5-LSTM-Based Diagnosis of PMSM Stator Faults Using Vibration Signals Across Different Fault Severities, has been accepted for presentation at the 2025 IEEE Conference on Power Electronics and Renewable Energy (CPERE).
  • [April, 2025]: Our paper, Bearing Fault Diagnosis in Induction Motors Using Low-Cost Triaxial ADXL355 Accelerometer and a Hybrid CWT-DCNN-LSTM Model, has been accepted for publication in IEEE Access..
  • [October, 2024]: Our paper, Enhanced Fault Diagnosis in Rotating Machinery Using a Hybrid CWT-LeNet-5-LSTM Model: Performance Across Various Load Conditions, has been accepted for publication in IEEE Access..
  • [August, 2024]: Our paper, Comparison of ANN and CNN Models for Misfire Detection in a Vehicle Engine at Different RPMs Using a Low-Cost ADXL1002 Accelerometer, has been accepted for presentation at the IEEE SPA 2024 Conference.

Contact Information

  • Email: AhsanMuhammad@aol.com

Disclaimer

This is a personal website. The opinions expressed are mine and do not necessarily represent the views of my employer.
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© Muhammad Ahsan 2025.