Doctor Mobarak Hossain

Dr. Mobarak Hossain is an Associate Lecturer in Mechanical Engineering at Western Sydney University (WSU), Australia, specialising in structural dynamics, vibration-based condition monitoring, and intelligent sensing systems. He received his PhD in Mechanical Engineering from WSU in 2018.

His research sits at the intersection of experimental mechanics, advanced manufacturing, and AI-driven diagnostics, with a focus on real-world industrial applications. He develops data-driven monitoring systems for rotating machinery, additive manufacturing processes, and infrastructure systems.

Prior to his current role, Dr. Hossain held academic and research positions at the University of New South Wales (UNSW), the University of Technology Sydney (UTS), and Western Sydney University, contributing to interdisciplinary research and teaching in vibration, structural dynamics, and materials engineering.

Dr. Hossain’s research focuses on the development of advanced, data-driven techniques for condition monitoring and fault diagnostics in mechanical systems. His work integrates experimental vibration analysis, signal processing, and emerging AI-based methods to improve reliability and performance in engineering applications.

Key research areas include:

• Experimental vibration and acoustic analysis (modal analysis, FRF, and time–frequency methods)
• Data-driven predictive maintenance for rotating machinery and manufacturing systems, with scope for integration of machine learning methods
• Structural health monitoring using smart sensing technologies
• Dynamic behaviour analysis and defect detection in advanced manufacturing systems

His research supports Industry 4.0 initiatives, smart infrastructure, and sustainable manufacturing by enabling early fault detection and improved system reliability. 

His research uniquely combines high-fidelity experimental measurements with data-driven analysis to enable practical and scalable condition monitoring solutions.

• Condition monitoring
• Predictive maintenance
• Structural dynamics
• Vibration analysis
• Modal analysis
• Frequency response function (FRF)
• Rotating machinery diagnostics
• Advanced Manufacturing Systems
• Smart sensing systems
• Structural health monitoring

Available HDR Projects (PhD / MPhil)

Dr. Hossain is seeking highly motivated students to work on research in data-driven condition monitoring, smart sensing, and advanced manufacturing systems. These projects combine experimental vibration analysis with signal processing and data-driven techniques to address real-world engineering challenges.

Research opportunities include:

Data-Driven Condition Monitoring for Smart Manufacturing – develop signal-processing and data-driven techniques for early fault detection in rotating machinery and manufacturing systems, with scope for integration of machine learning methods.

Advanced Vibration Diagnostics for Rotating Machinery – investigate fault mechanisms (e.g., cracks, imbalance, misalignment) using modal analysis, frequency response functions (FRF), and time–frequency signal processing.

Smart Structural Health Monitoring Systems – design and implement sensing and data analysis techniques for real-time monitoring of structural and mechanical integrity.

Dynamic Behaviour of Advanced Manufacturing Systems – analyse vibration characteristics and detect defects in manufacturing systems under varying material properties and process parameters.

These projects offer opportunities to work with state-of-the-art experimental facilities, develop publishable research, and collaborate on industry-relevant problems aligned with Industry 4.0.

Prospective candidates with backgrounds in mechanical engineering, mechatronics, signal processing, or data analytics are encouraged to apply.