Rate My Professor Nurfatihah Syalwiah Rosli

Dr. Nurfatihah Syalwiah Rosli is a researcher at Curtin University, listed in the Artificial Intelligence discipline since 14 May 2024 and the Renewable Energy discipline. Her research emphasizes predictive maintenance, fault detection, and modeling for industrial equipment, particularly in electrical and electronics engineering applications relevant to oil and gas platforms, compressors, motors, and gas metering systems. She employs techniques such as multiple linear regression, artificial neural networks, recurrent neural networks, particle swarm optimization, principal component analysis, and long short-term memory models to develop predictive interfaces, detect sensor abnormalities, and forecast system failures. This work supports reliability and efficiency in engineering operations.

Among her key publications, 'Development of Predictive Maintenance Interface Using Multiple Linear Regression' (T. Abbasi et al., 2018, International Conference on Intelligent and Advanced Systems, 36 citations) introduces a regression-based interface for maintenance prediction. 'Predictive Maintenance of Air Booster Compressor (ABC) Motor Failure using Artificial Neural Network Trained by Particle Swarm Optimization' (N.S. Rosli et al., 2019, IEEE Student Conference on Research and Development, 12 citations) optimizes neural networks for motor failure prediction. 'Modeling of High Voltage Induction Motor Cooling System Using Linear Regression Mathematical Models' (N.S. Rosli et al., 2022, PLOS ONE, 10 citations) models cooling systems for induction motors. Additional contributions include 'Combined Experimental and Field Data Sources in a Prediction Model for Corrosion Rate Under Insulation' (N.R.A. Burhani et al., 2019, Sustainability, 8 citations), 'Neural Network Model with Particle Swarm Optimization for Prediction in Gas Metering Systems' (N.S. Rosli et al., 2016, 10 citations), 'Fast Approach for Automatic Data Retrieval Using R Programming Language' (T.D. Chung et al., 2016, 16 citations), 'Intelligent Prediction System for Gas Metering System using Particle Swarm Optimization in Training Neural Network' (N.S. Rosli et al., 2017, Procedia Computer Science, 8 citations), and 'Application of Principal Component Analysis vs. Multiple Linear Regression in Resolving Influential Factor Subject to Air Booster Compressor Motor Failure' (N.S.B. Rosli et al., 2018, 8 citations). With 16 publications accumulating 99 citations on ResearchGate and teaching roles at Universiti Malaysia Sabah including Thermodynamics Engineering, she also served as a session chair at the GECOST 2025 conference.