Staff Profile

Biography

Dr. Albe Chai obtained his Bachelor of Engineering (Hons) in Electrical and Electronic from Swinburne University of Technology, Sarawak Campus in 2022. After that, he continued his academic journey at the same institution for PhD studies and successfully completed it in 2025. In the same year, he joined Swinburne Sarawak as a lecturer under the Faculty of Engineering, Computing and Science.

His research interests include the Internet of Things, Artificial Intelligence, and smart systems, with applications in areas such as road safety, microalgae cultivation, disease outbreak modelling, and green energy. He also contributed to the academic community as a peer reviewer for journals such as Engineering Applications of Artificial Intelligence and IEEE Potentials.

Research Interests

• Internet of Things (IoT) Solutions
• Artificial Intelligence and Applications
• Smart Systems

Professional Membership

• Graduate Engineer, Board of Engineers Malaysia (BEM)
• Member, Institute of Electrical and Electronics Engineers (IEEE)

PhD/Master by Research Opportunities

Potential research higher degree candidates are welcome to enquire about postgraduate opportunities in the areas listed above. Please e-mail [email protected] for more information.

Publications

• Journal Paper: Chai, ABZ, Lau, BT, Ginjom, IRH, Tee, MKT, Show, PL & Palombo, E 2025, ‘Development of a Smart Incubator for Microalgae Cultivation in Food Production: A Case Study of Spirulina’, Computers and Electronics in Agriculture, vol. 233, 110163. DOI: 10.1016/j.compag.2025.110163
• Journal Paper: Chai, ABZ, Lau, BT, Tee, MKT & McCarthy, C 2024, ‘Enhancing road safety with machine learning: Current advances and future directions in accident prediction using non-visual data’, Engineering Applications of Artificial Intelligence, vol. 137. DOI: 10.1016/j.engappai.2024.109086
• Journal Paper: Chai, ABZ, Lau, BT, Tee, MKT & McCarthy, C 2023, ‘Comparative analysis of regional variations in road traffic accident patterns with association rule mining’, EAI Endorsed Transactions on Pervasive Health and Technology, vol. 9. DOI: 10.4108/eetpht.9.3173
• Conference Paper: Chai, ABZ, Lau, BT, Tee, MKT & Show, PL 2025, ‘Enhancing Machine Learning-Based Microalgae Growth Prediction with Feature Selection’, 2025 8th International Conference on Algorithms, Computing and Artificial Intelligence (ACAI), Nanjing, China. DOI: 10.1109/ACAI68217.2025.11406478
• Conference Paper: Chai, ABZ, Lau, BT, Tee, MKT & Show, PL 2025, ‘A Machine Learning-Based Microalgae Growth Prediction Model’, 2025 IEEE 8th International Conference on Computer and Communication Engineering Technology (CCET), Beijing, China. DOI: 10.1109/CCET66260.2025.11199444
• Conference Paper: Chai, ABZ, Lau, BT, Tee, MKT & McCarthy, C 2024, ‘R-TAP: A Cloud-Based Multi-Region Road Traffic Accident Severity Prediction Model’, 2024 IEEE Industrial Electronics and Applications Conference (IEACon), Kuala Lumpur, Malaysia. DOI: 10.1109/IEACon61321.2024.10797326
• Conference Paper: Chai, ABZ, Lau, BT, Tee, MKT, Ginjom, IRH, Philimon, SP, Show, PL, Palombo, E, Chua, C, Bong, PC & Lee, CK 2024, ‘Smart incubator for small-scale algae cultivation with Internet of Things’, 4th International Conference on Internet of Things and Smart City (IoTSC 2024), Hangzhou, China. DOI: 10.1117/12.3034987
• Conference Paper: Chai, ABZ, Lau, BT, Tee, MKT & McCarthy, C 2023, ‘Road Traffic Accident Pattern Analysis with Data Mining’, 2023 12th International Conference on Awareness Science and Technology (iCAST), Taichung, Taiwan. DOI: 10.1109/iCAST57874.2023.10359286