Personal statement

Dr. Ding Ze Yang is a Lecturer in the Department of Electrical and Robotics Engineering at Monash University Malaysia. He obtained his Bachelor's degree and PhD in Engineering from the same university in 2019 and 2023, respectively. His research focuses on industrial AI, with a primary emphasis on developing data-driven soft sensors for process monitoring in industrial systems. He has published in several high-impact factor journals, such as IEEE Transactions on Industrial Informatics and Soft Robotics. Dr. Ding's research interests include deep learning, data-driven modeling, process monitoring, soft sensor, machine intelligence, and autonomous systems.

Academic degrees

• Doctor of Philosophy in Engineering, Monash University Malaysia, 2023
• Degree in Electrical and Computer Systems Engineering, 2019

Professional affiliation

Member of National Professional Bodies

• Board of Engineers Malaysia (BEM),  Graduate Engineer

Member of International Professional Bodies

N/A

Research Interests

Dr. Ding’s research focuses on industrial AI, which refers to the use of AI technologies such as deep learning, computer vision, and robotics to improve industrial applications. Industrial AI is utilized to enhance manufacturing processes, increase operational efficiency, and reduce costs in industries such as manufacturing, transportation, energy, and logistics. Some examples of industrial AI applications include predictive analytics, process optimization, intelligent control systems, and autonomous robotics. These applications rely on large amounts of data generated from industrial processes and sensors, which are analyzed using AI algorithms to improve the performance and efficiency of the systems. Industrial AI has the potential to revolutionize the way we manufacture products and manage industrial processes, making them more efficient, cost-effective, and environmentally sustainable.

There are many exciting research projects to explore in the field of industrial AI, including:

• Monitoring and Control of Industrial Processes using Deep Learning
• Fault Diagnosis and Predictive Maintenance
• Knowledge Discovery for Explainable AI in Industrial Systems
• Reinforcement Learning for Process Optimization
• Autonomous Systems for Transportation and Logistics

Presented paper entitled “Classification of Transformer Core and Winding Conditions from SFRA Measurement” for the 4th Symposium on Image Processing, Image Analysis and Real-Time Imaging (IPIARTI 2013) organized by IEEE Signal Processing Society Malaysian Chapter and the Center for Signal Processing and Control Systems (CSPaCS), on 9th May 2013 at Universiti Tenaga Nasional, Putrajaya Campus, Selangor, Malaysia.

Presented a paper entitled “Analysis of Transformer Core and Winding Conditions from SFRA Measurement Using Statistical Parameter” at the Science & Engineering Technology National Conference 2013 (SETNC 2013) on the 3rd and 4th July 2013 at Dewan Utama Universiti Kuala Lumpur Malaysia France Institute.

Published a paper entitled “Development of Risk-Based Distribution System Planning Methodology and Applications” at the Conference of the Electric. Power Supply Industry 2018 (CEPSI 2018) on the 17th September 2018 at Kuala Lumpur Convention Centre (KLCC).

Published in a UTHM Engineering handbook at UTHM “An Approach to Islanded Distribution Network Using Energy Storage System Powered by Renewable Energy” in 2019.

Presented at KLCC - Conservation of Voltage Reduction (CVR) - Potential Techniques Towards Greener and Efficient Electricity Supply in 2019.

Presented in an Asian Utility Conference “Conservation Voltage Reduction (CVR) Applications for Malaysia Residential End Load – An Insight” in 2019.

Published in a UTHM Engineering handbook at UTHM “Silver Corrosion Failure Phenomenon Diagnostics and Mitigation in Power Transformers” in 2019.

Published in a UTHM Engineering handbook at UTHM “Assessment of Electromagnetic Field (EMF) In a Primary Substation” in 2019.

Published a paper entitled “Analysis of Conservation Voltage Reduction (CVR) Factor for Various Types of Loads” at the International Journal of Engineering Applied Sciences and Technology, 2020, vol. 5, Issue 4, ISSN No. 2455-2143, Pages 66-72.

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