
Keywords
Fields of Research (FoR)
Computer vision, Deep learning, Machine learning, Image processing, Artificial intelligenceBiography
Personal website - https://donggong1.github.io/
Dr Dong Gong is a Lecturer and ARC DECRA Fellow in the School of Computer Science and Engineering. He is also an Adjunct Lecturer with the Australian Institute for Machine Learning (AIML) of The University of Adelaide. Befor joining UNSW, he was a Research Fellow at Australian Institute for Machine Learning (AIML), a Principal Researcher at Centre for Augmented Reasoning (CAR), The University of...view more
Personal website - https://donggong1.github.io/
Dr Dong Gong is a Lecturer and ARC DECRA Fellow in the School of Computer Science and Engineering. He is also an Adjunct Lecturer with the Australian Institute for Machine Learning (AIML) of The University of Adelaide. Befor joining UNSW, he was a Research Fellow at Australian Institute for Machine Learning (AIML), a Principal Researcher at Centre for Augmented Reasoning (CAR), The University of Adelaide.
His research area is in Computer Vision, Machine Learning, Deep Learning, Image Restoration, and Artificial Intelligence. He has been actively publising in the top venues, including CVPR, ICCV, ECCV, AAAI, IJCV, TIP, etc. He is focusing on developing generalizable, realiable, and efficient computer vision (CV) and machine learning (ML) approaches for the applciations in real-world scenarios.
His current research topics include:
- machine learning with non-ideal supervision in real-world scenarios, e.g.,
- continual learning
- unsupervised/semi-supervised/domain-adaptive learning
- low/high-level computer vision:
- image restoration, e.g., deblurring/deconvolution, super-resolution, high dynamic range imaging, etc.
- image/video understanding
- 3D scene reconstruction and understanding
- deep learning
- memory-augmented deep learning
- deep learning with sparsity/optimization
- novelty/outlier/anomaly detection
- neural relational inference
- interdisciplinary problems
- mining with data augmentation, e.g., mineral exploration with CV and ML technologies
- agriculture innovation, e.g., soil trait impact analysis
My Research Supervision
Areas of supervision
I am continually seeking highly motivated PhD, MPhil, or visiting students with a passion and strong background for computer vision and machine learning.
Please send me your CV and transcripts via email if you are interested.
To UNSW master and undergraduate students:
I can take a limited number of Honours or Master students working on research projects in machine learning, deep learning, and/or computer vision.
You should have good GPA/WAN (courses about related topics and math) and programming experience in Python.
More details of my research can be found on my personal website.
Contact
ORCID as entered in ROS
