Dr Kenneth Li-minn Ang received his BEng (Hons) and PhD degrees from Edith Cowan University in Australia. He is currently Professor of Electrical and Computer Engineering at the School of Science, Technology and Engineering at University of the Sunshine Coast (UniSC).
Dr Ang has worked in Australian and UK universities including Monash University, University of Nottingham, ECU, CSU and Griffith University. Prior to joining UniSC, he was an Associate Professor at Griffith University.
His research interests are in computer, electrical and systems engineering including Internet of Things, intelligent systems and data analytics, machine learning, visual information processing, embedded systems, wireless multimedia sensor systems, reconfigurable computing (FPGA) and the development of innovative technologies for real-world systems including smart cities, engineering, agriculture, environment, health and defence.
Dr Ang has published three research books and over 200 papers in journals, book chapters and international refereed conferences and has achieved over 3 million in grant income from government and industry. He has supervised or co-supervised over 25 HDR including 15 PhD students to completion. He serves on the editorial board or committees of several journals and international conferences. He is a Fellow of Engineers Australia, a Senior Member of the IEEE and a Senior Fellow of the Higher Education Academy (UK).
Professional memberships
- Fellow of Engineers Australia
- IEEE Senior member
- HEA Fellow
Research areas
- application-specific Internet of Things, wireless sensor-based systems
- intelligent systems, machine learning, data analytics
- multimedia and visual information processing
- reconfigurable computing and embedded systems
- innovative technologies and development of real-world applications and computational systems
Teaching areas
- ENG106 Engineering Computing
- ELC200 Digital Logic and Computer Programming
- ELC404 Advanced Digital and Embedded Systems
Program coordinator
Selected recent publications 2023-2025
Singh, H., Ang, L. M., & Srivastava, S. K. (2025). Benchmarking artificial neural networks and U-net convolutional architectures for wildfire susceptibility prediction: Innovations in geospatial intelligence. IEEE Transactions on Geoscience and Remote Sensing.
He, Y., Seng, K. P., & Ang, L. M. (2025). Collaborative AI Dysarthric Speech Recognition System with Data Augmentation using Generative Adversarial Neural Network. IEEE Transactions on Neural Systems and Rehabilitation Engineering.
Singh, H., Ang, L. M., Paudyal, D., Acuna, M., Srivastava, P. K., & Srivastava, S. K. (2025). A Comprehensive Review of Empirical and Dynamic Wildfire Simulators and Machine Learning Techniques used for the Prediction of Wildfire in Australia. Technology, Knowledge and Learning, 1-34.
Ngharamike, E., Ang, L. M., Wang, M., & Seng, K. P. (2025). Intra-grid location estimation of smartphone videos using ENF extraction and an improved super-pixel technique. Scientific Reports, 15(1), 19614.
Singh, H., Ang, L. M., & Srivastava, S. K. (2025). Active wildfire detection via satellite imagery and machine learning: An empirical investigation of Australian wildfires. Natural Hazards, 1-24.
Ang, L. M., Su, Y., Seng, K. P., & Smith, J. S. (2025). Customized Binary Convolutional Neural Networks and Neural Architecture Search on Hardware Technologies. IEEE Nanotechnology Magazine.
H. Xu, K. P. Seng, L. -M. Ang, W. Wang and J. Smith, "Graph Split Federated Learning for Distributed Large-Scale AIoT in Smart Cities," IEEE Open Journal of the Computer Society, vol. 6, pp. 1027-1040, 2025.
Rahman, M. A., Ang, L. M., Sun, Y., & Seng, K. P. (2025). A deep embedded clustering technique using dip test and unique neighbourhood set. Neural Computing and Applications, 37(3), 1345-1356.
He, Y., Seng, K. P., Lim, C. S., & Ang, L. M. (2025). Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction. Advanced Intelligent Systems, e202500873.
Singh, H., Ang, L. M., Lewis, T., Paudyal, D., Acuna, M., Srivastava, P. K., & Srivastava, S. K. (2024). Trending and emerging prospects of physics-based and ML-based wildfire spread models: A comprehensive review. Journal of Forestry Research, 35(1), 135.
Saleem, M. I., Saha, S., Izhar, U., & Ang, L. (2024). Bi-Layer Model Predictive Control strategy for techno-economic operation of grid-connected microgrids. Renewable Energy, 236, 121441.
He, Y., Seng, K. P., & Ang, L. M. (2024). CycleGAN*: Collaborative AI Learning with Improved Adversarial Neural Networks for Multi-modalities Data. IEEE Transactions on Artificial Intelligence.
Xu, H., Seng, K. P., Ang, L. M., & Smith, J. (2024). Decentralized and distributed learning for AIoT: A comprehensive review, emerging challenges, and opportunities. IEEE Access, 12, 101016-101052.
Chen, J., Seng, K. P., Smith, J., & Ang, L. M. (2024). Situation awareness in ai-based technologies and multimodal systems: Architectures, challenges and applications. IEEE Access, 12, 88779-88818.
Su, Y., Ang, L. M., Seng, K. P., & Smith, J. (2024). Deep Learning and Neural Architecture Search for Optimizing Binary Neural Network Image Super Resolution. Biomimetics, 9(6), 369.
Ngharamike, E., Ang, L. M., Seng, K. P., & Wang, M. (2023). ENF based digital multimedia forensics: Survey, application, challenges and future work. IEEE Access, 11, 101241-101272.
Ijemaru, G. K., Ang, L. M., & Seng, K. P. (2023). Optimizing energy consumption and provisioning for wireless charging and data collection in large-scale WRSNs with mobile elements. IEEE Internet of Things Journal, 10(20), 17585-17602.
Seng, K. P., Ang, L. M., Ngharamike, E., & Peter, E. (2023). Ridesharing and crowdsourcing for smart cities: technologies, paradigms and use cases. IEEE Access, 11, 18038-18081.
Rahman, M. A., Ang, L. M., & Seng, K. P. (2023). An automated identification approach for partial discharge detection using density-based clustering without user inputs. IEEE Transactions on Artificial Intelligence, 5(1), 310-320.
Professor Ken Ang's specialist areas of knowledge include computer, electrical and systems engineering. intelligent systems and data analytics. wireless multimedia sensor systems, reconfigurable computing (FPGA) and the development of innovative technologies for real-world systems including smart cities, engineering, agriculture, environment, health and defence.