Homepage - https://donggong1.github.io/
Dong Gong is a Senior Lecturer and ARC DECRA Fellow (2023 - 2026) in the School of Computer Science and Engineering (CSE), UNSW Sydney. He is also an Adjunct Lecturer with the Australian Institute for Machine Learning (AIML) of The University of Adelaide. Before joining UNSW, he was a Research Fellow at the Australian Institute for Machine Learning (AIML) and a Principal Researcher at the Centre for Augmented Reasoning (CAR) of the University of Adel...
Homepage - https://donggong1.github.io/
Dong Gong is a Senior Lecturer and ARC DECRA Fellow (2023 - 2026) in the School of Computer Science and Engineering (CSE), UNSW Sydney. He is also an Adjunct Lecturer with the Australian Institute for Machine Learning (AIML) of The University of Adelaide. Before joining UNSW, he was a Research Fellow at the Australian Institute for Machine Learning (AIML) and a Principal Researcher at the Centre for Augmented Reasoning (CAR) of the University of Adelaide.
His research area is Computer Vision (CV), Machine Learning (ML), Deep Learning (DL), and general Artificial Intelligence (AI) topics. He has been actively publishing in the top venues, including CVPR, ICCV, ECCV, NeurIPS, ICLR, AAAI, IJCV, TIP, etc. He is focusing on developing generalizable, reliable, and efficient computer vision (CV) and machine learning (ML) approaches for applications in real-world scenarios.
His current research topics include:
- machine learning methods and tasks with non-ideal supervision, e.g.,
- continual learning
- out-of-distribution(OOD)/anomaly/novelty/outlier detection
- semi-supervised/domain-adaptive/unsupervised 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 neural network (DNN) designing and training, e.g.,
- memory mechanism in deep learning
- training and adaptation of pre-trained large foundation models
- interdisciplinary problems
- mining with data augmentation, e.g., mineral exploration with CV and ML technologies
- agriculture innovation, e.g., soil trait impact analysis
I am continually seeking highly motivated PhD, MPhil, and visiting students with passion and a strong background in computer vision and machine learning.
Current undergraduate students or master by course students at UNSW are encouraged to contact me if you are interested in research degrees (Master by research or PhD) or research projects (honors thesis project or master research project) in CV, ML, and related topics.
Please check the details and email me your CV and transcripts if you are interested.
- Publications