John Zeyang Zhou is a PhD student specialising in Artificial Intelligence (AI) and Data Analytics at UTS. He has expertise in machine learning (ML) and deep learning across various domains and is eager to apply research and teaching experience to drive innovation and contribute to advancements in AI.

John completed his UTS Bachelor of Science in Information Technology (First Class Honours) in 2022 where his research project investigated AI and ML in health insurance fraud leakage detection. He designed and implemented anomaly detection models to identify fraudulent claims and enhanced the efficiency of the claims processing system by automating the identification of suspicious claims.

His PhD is focused on the use of AI and ML in battery management systems. In this project he seeks to develop ML algorithms to predict battery degradation, optimise charging cycles and implement a real-time monitoring and management system to reduce energy consumption.

In 2023 he also worked on a research project to use deep learning to classify neurodegenerative diseases. This involved leveraging multiple deep learning architectures to analyse neurodegenerative disease patterns within a gait dynamics dataset and resulted in enhanced diagnostic capabilities.

While maintaining his strong focus on research, John works as a casual academic at UTS and a research and teaching assistant. He is currently supervising several Honours, Capstone and Research Masters Students.

John has published several research papers and presented a paper at the Robotics, Control and Vision Engineering Conference (2023). He is also a member of the Institute of Electrical and Electronics Engineers.

Incredibly passionate about his work, John's ultimate aim is to leverage AI to contribute to a sustainable future by addressing critical environmental and societal challenges through innovative research, education, and practical applications.