Dong Gong

I am currently a Lecturer (a.k.a. Assistant Professor) at the School of Computer Science and Engineering, The University of New South Wales (UNSW Sydney), Australia. I am also an Adjunct Lecturer with the Australian Institute for Machine Learning (AIML) of The University of Adelaide. Previously, I was a Research Fellow at the Australian Institute for Machine Learning (AIML), a Principal Researcher at Centre for Augmented Reasoning (CAR), The University of Adelaide, working with Prof. Anton van den Hengel, Prof. Qinfeng (Javen) Shi and Prof. Chunhua Shen. I obtained my PhD and B.S. in computer science from Northwestern Polytechnical University in 2018 and 2012, advised by Prof. Yanning Zhang. During my PhD studies, I spent two years at The University of Adelaide, working with Javen and Anton. I am recruiting PhD/MPhil/visiting students in computer vision and machine learning. Please feel free to drop me an email with your CV. [Github] [Google Scholar] [Twitter] [UNSW Homepage]

News

• (Sep  2022) I am awarded ARC Discovery Early Career Researcher Award (DECRA) to start 2023.

• (Sep  2022) 1 paper (about DAG learning) accepted to appear at NeurIPS 2022

• (Mar 2022) 1 paper (Continual Learning with Sparse Neural Networks) accepted to appear at CVPR 2022

• (Jan  2022) Check the article summarizing part of our works using ML to help agriculture innovation.

• (Sep  2021) 1 paper (about HDR imaging) accepted to appear in IJCV.

• (July 2021) 1 paper (Memory-augmented Neural Relational Inference) accepted to appear at ICCV 2021

• (July 2021) I will be a co-lecturer on Introduction to Statistical Machine Learning at UoA this semester, and give guest lectures at Deep Learning Fundamentals.

• (Dec 2020) 1 paper (unpaired domain-adaptive learning for realistic SR) accepted to appear in TIP

• (Oct  2020) 1 paper (learning attention model for vehicle retrieval) accepted to appear in TITS

• (Sep  2020) I am giving lectures at UoA Deep Learning Fundamentals on RNN, Attention, & Memory Networks.

• (July 2020) 1 paper (memory network for 3D point cloud with long-tail dist.) accepted to appear at ECCV 2020

• (Jan  2020) 1 paper (on learning to optimize for image deconv.) accepted to appear in TNNLS

• (July 2019) 1 paper (MemAE) accepted to appear at ICCV 2019

• (July 2019) 1 paper (about Sparse PCA) accepted to appear in TKDE

• (Jun  2019) 2nd Prize of OZ Minerals Explorer Challenge as part of DeepSightX team

• (Mar 2019) 1 paper accepted to appear in TKDE

• (Feb  2019) 4 papers accepted to appear at CVPR 2019

• (Nov 2018) 1 paper (on Blind Image Quality Assessment) accepted to appear in TIP

• (Oct  2018) 1 paper (about MRF based Compressive Sensing) accepted to appear in TIP

• (Sep  2018) 1 paper (MPTV) accepted to appear in TIP

• (July 2018) 2 papers accepted to appear at ECCV 2018

• (Oct  2017) Participated in ICCV 2017 Doctoral Consortium with a travel award

• (July 2017) 1 paper accepted to appear at ICCV 2017

• 1 paper accepted to appear at CVPR 2017

• 1 new arXiv paper on deep learning for motion estimation and blur removal

• 1 paper accepted to appear at AAAI 2017 as an oral

Research Interests

I have broad interests in machine learning and computer vision. My current major research topics are about:

• low/high-level computer vision

• deep/sparse modeling, optimization and learning, e.g.,
  - memory mechanism in deep learning
  - deep learning with sparsity
  - optimization + learning/sparsity

• learning with low supervision, e.g.,
  - continual/unsupervised/semi-supervised/domain-adaptive learning

• interdisciplinary problems

Contact

Office: Level 4, Building K17, UNSW, Sydney 2052, Australia

Email : edgong01 at gmail.com, dong.gong at unsw.edu.au