معرفی
Longbing Cao is a prominent academic researcher in data science and artificial intelligence, currently holding dual affiliations with Macquarie University's School of Computing in Sydney, Australia, and the University of Technology Sydney (UTS). He leads the Data Science Lab and has established himself as a leading authority in machine learning, data mining, and anomaly detection research with a prolific publication record spanning over two decades.
Dr. Cao's research encompasses multiple critical domains within data science, with particular expertise in deep learning for anomaly detection, time series analysis, recommender systems, and behavior informatics. His scholarly work bridges theoretical foundations with practical applications across diverse industries including finance, cybersecurity, and e-commerce. He has pioneered innovative approaches in coupled behavior analysis, representation learning, and cross-domain collaborative filtering that have significantly advanced these fields. His research demonstrates a consistent trajectory from foundational data mining techniques to sophisticated deep learning methodologies.
His publication record shows remarkable impact with 240 publications as of 2025 and 4,725 total citations. His highly influential survey papers have shaped research directions across multiple domains, with "Deep Learning for Anomaly Detection: A Review" (2021) accumulating over 1,600 citations and 25,586 downloads, establishing it as a seminal reference in the field. His recent work (2025) focuses on cutting-edge topics including diffusion models (SepDiff, ProgDiffusion), dynamic spectral graph analysis, and non-stationary time series modeling, reflecting his position at the forefront of AI research evolution.
- Data Science: A Comprehensive Overview (2017) - 298 citations, 41,677 downloads
- Data science: challenges and directions (2017) - 87 citations, 31,525 downloads
- AI in Finance: Challenges, Techniques, and Opportunities (2022) - 201 citations, 21,892 downloads
- A Survey on Session-based Recommender Systems (2021) - 346 citations, 4,563 downloads
As a research leader, Dr. Cao has mentored numerous students and collaborators, contributing significantly to the development of next-generation data science researchers. His Data Science Lab serves as an interdisciplinary hub where computer scientists, statisticians, and domain experts collaborate to tackle complex data challenges. The lab's research spans theoretical advancements in machine learning algorithms to practical implementations with tangible real-world impact across multiple sectors.
