I am a researcher in computational intelligence and human-centred computing. My research focuses on deep learning for signal processing, pattern recognition and information integration, and covers various technological contexts such as brain-computer interfaces, human-computer interaction, biometrics and information systems. I have designed and developed deep learning models and frameworks for signal processing, feature retrieval, representation learning and pattern recognition in biometric systems, human-machine systems, information integration systems and recommender systems. Recently, I also expanded my work in other directions, including information security (especially in biometric systems), privacy and security aspects of AI, and AI for cyber-physical security in smart grids.
Shadi Abpeikar, Maryam Ghodrat, Terry Frankcombe and Min Wang, Li-ion Battery Fire Risk Mitigation Using Deep Learning Approach, UNSW Faculty Seed Funding (49,000 AUD), 2023-2024
Min Wang, Smart Grid Vulnerability and Defense Under Cascading Failure Attacks, UNSW DGFI Seed Funding (25,000 AUD), 2023
Min Wang, Kangjing Li, Jo Plested, Huadong Mo and Jiankun Hu, A Novel Deep Learning-based Algorithm for Online Classification, Identification, and Prediction of Cascading Cyber-physical Failures in Smart Grids, UNSW Research Funding (19,142 AUD), 2023
Christine Boshuijzen-van Burken, Nan Sun, Min Wang, Shabnam Kasra Kermanshahi and Jiankun Hu, Ethically Aligned AI Cyberbullying Detection Tools, UNSW Research Funding (23,110 AUD), 2023
My Research Supervision