Junbin Gao is currently Professor of Big Data Analytics in the University of Sydney Business School. Prior to this position, Junbin Gao was a Professor/Associate Professor of Computing in School of Computing and Mathematics at Charles Sturt University from 2005 to 2016. Professor Gao also held a position of Senior Lecturer/Lecturer at University of New English in Australia from 2001 to 2005, and he was a Professor of Applied Mathematics in the Department of Mathematics of Huazhong University of Science and Technology before he moved to Australian in November 2001. He also worked as a senior research fellow at University of Southampton in England between 1999 and 2001.

Junbin Gao is an International Standard expert in Machine Learning. His current research interests cover Statistical Machine Learning, Bayesian Inference, Computer Vision and Image Analysis, Data Mining and Big Data, Numerical Optimization, and Visualization. His research on Dimensionality Reduction was featured in an article published on 4 December 2012 by The Australian newspaper. Professor Junbin Gao is an active scholar in major smart computation on the world stage. He has been serving as an assessor of international standard for ARC since 2004. He is an associate editor for Journal of Probability and Statistics and Applied Computational Intelligence and Soft Computing. He serves as local chair or program member for more 50 international conferences such as ICCV, ECCV, CVPR, IJCAI, AAAI, PAKDD, IEEE SMC etc.

Professor Gao has published One monograph, 65 papers in leading journals, i.e. CORE (Computing Research and Education of Australia http://www.core.edu.au) Tier A/A* or top 25%/Q1 of JCR journals and 48 papers in leading conferences e.g. AAAI, IJCAI, CVPR, PAKDD, ICDM, SDM, IJCNN etc, included in a career total of 260 publications. My publications have received > 3366 citations and I have an h-index of 24 (Google scholar). I have also attracted more than $2 millions in research income (excluding research income granted in China), and supervised 8 PhD students to graduation.