
Dr Dong Gong
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Dr. Dong Gong is a Senior Lecturer and ARC DECRA Fellow (2023-2026) at the School of Computer Science and Engineering (CSE), The University of New South Wales (ºÚÁÏÍø´óʼÇ). He is also holding an adjunct position at the Australian Institute for Machine Learning (AIML) at The University of Adelaide. His research interests are in computer vision and machine learning. Recently, he has been focusing on machine learning challenges with dynamic requirements in an open-ended realistic world, including continual learning and more flexible learning paradigm, and their applications on foundation model and diffusion generative models. He has been actively serving the research community as Area Chair or reviewers for conferences such as CVPR, ICML, ICCV, NeurIPS, ACM MM, etc, and was awarded as outstanding reviewers for NeurIPS’18 and outstanding AC for ACM MM’24.
His current research topics include:
- learning with non-ideal supervision in dynamic real-world scenarios, e.g.,
- continual learning
- unsupervised/semi-supervised/domain-adaptive learning
- foundation model (e.g., LLMs, embedding models, Multimodal LLMs) training, adaptation, reuse, and alignment
- generative models
- high-level visual perception & low-level vision problems, e.g.,
- semantic and depth prediction
- image restoration and enhancement
- deep learning model design and optimization, e.g.,
- memory mechanism in deep learning
- interdisciplinary problems with of CV, ML, and DL technologies, e.g.,
- mining and agriculture, e.g., ,Ìý
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I am continually seeking highly motivated PhD, MPhil, and visiting students with passion and a strong background in computer vision and machine learning.Ìý
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Current undergraduate students or master by course students at ºÚÁÏÍø´óÊÂ¼Ç 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 ML, CV, and related topics.Ìý
Please check theÌýÌýand email me your CV and transcripts if you are interested.Ìý
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