Guansong Pang

Guansong Pang is a Research Fellow at the Australian Institute for Machine Learning, University of Adelaide, Australia, where he joined in September 2018. He received a PhD degree from University of Technology Sydney (UTS) in May 2019, wining the university-wide best doctorate dissertation award – UTS Chancellor’s Award List. His research interests are to explore elegant data mining and machine learning algorithms for abnormality and rarity detection, and to tackle real-world problems in healthcare, information security, safety in AI systems and physical worlds, and scientific discovery.

He publishes regularly in top AI and Data Science conferences and journals such as KDD, CVPR, AAAI, IJCAI, ICDM, ACM MM, CIKM, ACM Computing Surveys, IEEE TKDE, ACM TKDD, DMKD (Springer), JAIR, IP&M, Bioinformatics, IEEE TMI, etc. He serves as (senior) PC member of these prestigious conferences and reviewer of the top journals. He is a (leading) guest editor of Special Issues with IEEE Transactions on Neural Networks and Learning Systems on deep anomaly detection and IEEE Intelligent Systems on non-i.i.d. anomaly detection. He is the organization chair of the IJCAI’20 Workshop on Artificial Intelligence for Anomalies and Novelties.

He is a tenure-track faculty candidate for the Artificial Intelligence & Data Science, Machine Learning & Intelligence cluster.

Education

• Master of Philosophy (M.Phil.) Monash University (2014 — 2015)
• Master of Philosophy (M.Phil.) Guangdong University of Foreign Studies (2010 — 2013)
• Bachelor of Engineering Guangdong University of Foreign Studies (2006 — 2010)

Companies

• Assistant Professor Of Computer Science Singapore Management University (2022)
• Research Fellow University of Adelaide (2018 — 2021)
• Research Assistant University of Technology Sydney (2015 — 2015)