Anjin Liu

Anjin Liu is a Researcher at the Centre for Artificial Intelligence, Faculty of Engineering and Information Technology, University of Technology Sydney. His research focuses on Concept Drift, Adaptive Data Stream Learning, Multi-stream Learning, Machine Learning, and Big Data Analytics.

His work addresses challenges in nonstationary environments through innovative methods like evolving gradient boosting, ensemble diversity optimization, and dynamic drift detection. He develops real-time systems for applications such as train carriage load prediction in collaboration with Sydney Trains.

Scientific Contributions:

• Proposed EI-kMeans for drift detection via cluster-based histograms
• Developed Fuzzy Decision Trees to handle uncertainty in stream learning
• Advanced Multi-stream aggregation techniques for improved generalization

He is available for Masters Research or PhD student supervision and has received funding for real-time transportation analytics projects.