Research output per year
Research output per year
Personal profile
Biography
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.
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
Please do not hesitate to reach out for further inquiries regarding the research topics and opportunities.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Engineering, Doctor of Philosophy, Monash University Malaysia
1 Dec 2019 → 14 Mar 2023
Award Date: 15 Mar 2023
Electrical and Computer Systems Engineering, Bachelor of Engineering (Honours), Monash University Malaysia
26 Oct 2015 → 28 Jun 2019
Award Date: 16 Nov 2019
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A deep learning framework for soft robots with synthetic data
Sapai, S., Loo, J. Y., Ding, Z. Y., Tan, C. P., Baskaran, V. M. & Nurzaman, S. G., 4 Dec 2023, In: Soft Robotics. 10, 6, p. 1224-1240 17 p.Research output: Contribution to journal › Article › Research › peer-review
3 Citations (Scopus) -
A zero-shot soft sensor modeling approach using adversarial learning for robustness against sensor fault
Ding, Z. Y., Loo, J. Y., Nurzaman, S. G., Tan, C. P. & Baskaran, V. M., Apr 2023, In: IEEE Transactions on Industrial Informatics. 19, 4, p. 5891-5901 11 p.Research output: Contribution to journal › Article › Research › peer-review
16 Citations (Scopus) -
Cross-domain transfer learning and state inference for soft robots via a semi-supervised sequential variational bayes framework
Sapai, S., Loo, J. Y., Ding, Z. Y., Tan, C. P., Phan, R. C. W., Baskaran, V. M. & Nurzaman, S. G., 2023, Conference Proceedings - ICRA 2023. Hutchinson, S. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 552-559 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
2 Citations (Scopus) -
Robust multimodal indirect sensing for soft robots via neural network-aided filter-based estimation
Loo, J. Y., Ding, Z. Y., Baskaran, V. M., Nurzaman, S. G. & Tan, C. P., Jun 2022, In: Soft Robotics. 9, 3, p. 591-612 22 p.Research output: Contribution to journal › Article › Research › peer-review
33 Citations (Scopus) -
Predictive uncertainty estimation using deep learning for soft robot multimodal sensing
Ding, Z. Y., Loo, J. Y., Baskaran, V. M., Nurzaman, S. G. & Tan, C. P., Apr 2021, In: IEEE Robotics and Automation Letters. 6, 2, p. 951-957 7 p.Research output: Contribution to journal › Article › Research › peer-review
15 Citations (Scopus)
Activities
- 1 Non-HDR Supervisions
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ENG4701 Final Year Project (Semester 1, 2024)
Tan Wen Shan (Supervisor), Yuan Teng Hooi (Supervisor) & Ding Ze Yang (Supervisor)
26 Jan 2024 → 15 Nov 2024Activity: Other Teaching Engagements and non-HDR Supervisions › Non-HDR Supervisions