Dr Dong Gong

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