ProfIvor Tsang
Adjunct Professor
Australian Artifical Intelligence Institute
Orcid identifier0000-0001-8095-4637 (opens in a new tab)
- Adjunct ProfessorAustralian Artifical Intelligence Institute
BIO
Professor Ivor Tsang, in the School of Computer Science at UTS, is working at the forefront of big data analytics and Artificial Intelligence. His work is recognised internationally for its outstanding contributions to those fields.
An IEEE Fellow, ARC Future Fellow and Professor of AI at UTS, Ivor’s research focuses on transfer learning, deep generative models, learning with weakly supervision, big data analytics for data with extremely high dimensions in features, samples and labels, and their application to computer vision and pattern recognition.
He is also the Research Director of the Australian Artificial Intelligence Institute (AAII), the largest AI institute in Australia, with 35 faculty members and more than 200 PhD students. AAII is a world-leading research institute with a vision to develop theoretical foundations and advanced algorithms for AI, and drive progress in related areas such as computational intelligence, machine learning, and brain computer interface.
In 2013, Ivor received his ARC Future Fellowship for his outstanding research on big data analytics and large-scale machine learning.
In 2019, Ivor’s Journal of Machine Learning Research paper titled "Towards ultrahigh dimensional feature selection for big data" received the International Consortium of Chinese Mathematicians Best Paper Award.
In 2020, he was recognized as the AI 2000 AAAI/IJCAI Most Influential Scholar in Australia for his outstanding contributions to the field, between 2009 and 2019. His research on transfer learning was awarded the Best Student Paper Award at CVPR 2010 and the 2014 IEEE TMM Prize Paper Award.
Ivor is elevated to IEEE Fellow (2022) for his outstanding contributions to large-scale machine learning and transfer learning.
In addition, he received the IEEE TNN Outstanding 2004 Paper Award in 2007 for his innovative work on solving the inverse problem of non-linear representations.
He serves as a Senior Area Chair/Area Chair for NeurIPS, ICML, AAAI and IJCAI, the Steering Committee for ACML, the Editorial Board for JMLR, MLJ, JAIR and IEEE TPAMI, and the Partner Editor of Springer Nature Computer Science. He is also the Program Chair of ACML 2021.
An IEEE Fellow, ARC Future Fellow and Professor of AI at UTS, Ivor’s research focuses on transfer learning, deep generative models, learning with weakly supervision, big data analytics for data with extremely high dimensions in features, samples and labels, and their application to computer vision and pattern recognition.
He is also the Research Director of the Australian Artificial Intelligence Institute (AAII), the largest AI institute in Australia, with 35 faculty members and more than 200 PhD students. AAII is a world-leading research institute with a vision to develop theoretical foundations and advanced algorithms for AI, and drive progress in related areas such as computational intelligence, machine learning, and brain computer interface.
In 2013, Ivor received his ARC Future Fellowship for his outstanding research on big data analytics and large-scale machine learning.
In 2019, Ivor’s Journal of Machine Learning Research paper titled "Towards ultrahigh dimensional feature selection for big data" received the International Consortium of Chinese Mathematicians Best Paper Award.
In 2020, he was recognized as the AI 2000 AAAI/IJCAI Most Influential Scholar in Australia for his outstanding contributions to the field, between 2009 and 2019. His research on transfer learning was awarded the Best Student Paper Award at CVPR 2010 and the 2014 IEEE TMM Prize Paper Award.
Ivor is elevated to IEEE Fellow (2022) for his outstanding contributions to large-scale machine learning and transfer learning.
In addition, he received the IEEE TNN Outstanding 2004 Paper Award in 2007 for his innovative work on solving the inverse problem of non-linear representations.
He serves as a Senior Area Chair/Area Chair for NeurIPS, ICML, AAAI and IJCAI, the Steering Committee for ACML, the Editorial Board for JMLR, MLJ, JAIR and IEEE TPAMI, and the Partner Editor of Springer Nature Computer Science. He is also the Program Chair of ACML 2021.
PROFILE TYPE
- Academic
AVAILABILITY
- Masters Research or PhD student supervision