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Yang Song

ARC Future Fellow, UNSW Scientia Fellow, Senior Lecturer
Research Theme: AI and Computer Vision

School of Computer Science and Engineering
University of New South Wales

Office: Room 401E, Building K17
Email: yang.song1 AT unsw.edu.au
Google Scholar        UNSW Researcher        DBLP

About Me

I am currently an ARC Future Fellow, UNSW Scientia Fellow and Senior Lecturer (Assistant Professor) at the School of Computer Science and Engineering, UNSW Sydney, Australia. I graduated with a BEng (Hons1) in Computer Engineering from Nanyang Technological University, Singapore, and obtained a PhD degree in Computer Science from the University of Sydney in 2013.

I received the highly competitive Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) in 2015, and was an ARC DECRA Fellow at the University of Sydney before joining UNSW as a Lecturer in 2018. In 2019, I received the prestigious ARC Future Fellowship, which provides support for excellent mid-career researchers to undertake high quality research in areas of national and international benefit. In 2020, I was awarded a Scientia Fellowship from UNSW, which supports career development of outstanding researchers.

News

Multiple PhD scholarships are available, which are well funded by my ARC Future Fellowship and UNSW Scientia Fellowship.

A list of sample research topics in Computer Vision and Biomedical Imaging can be found at my UNSW Researcher site. You are welcome to propose alternative research topics in this field.

I also have a strong interest in integrating knowledge representation with learning. A list of research topics can be found here.

Interested candidates with relevant academic background are strongly encouraged to apply. Please send me an email including your CV and transcripts.

Research Interests

My research interests include Computer Vision, Biomedical Image Analysis, Machine and Deep Learning, and General AI.

My current research mainly focuses on the development of machine and deep learning algorithms for computer vision problems such as:

  • Abnormality detection and segmentation

  • Morphological analysis in microscopy images

  • Cell segmentation and tracking

  • Biomarker detection and analysis

  • General image classification

  • Object detection and recognition

  • 3D image reconstruction

  • Action recognition and video analysis

  • Visual question answering

Publications

I have produced over 100 publications including papers in TMI, MedIA, NeuroImage, BMC Bioinformatics, CVPR, ICCV, AAAI, IJCAI, and MICCAI.

A full list of my publications can be seen from my Google Scholar.

Some selected recent publications:

  • D. Liu, D. Zhang, Y. Song, F. Zhang, L. O'Donnell, H. Huang, M. Chen, and W. Cai. Unsupervised instance segmentation in microscopy images via panoptic domain adaptation and task re-weighting. CVPR 2020.

  • C. Zhang, Y. Song, L. Yao, and W. Cai. Shape-oriented convolutional neural network for point cloud analysis. AAAI 2020.

  • D. Liu, D. Zhang, Y. Song, C. Zhang, F. Zhang, L. O'Donnell, and W. Cai. Nuclei segmentation via a deep panoptic model with semantic feature fusion. IJCAI 2019.

  • H. Jia, Y. Song, H. Huang, W. Cai, and Y. Xia. HD-Net: Hybrid discriminative network for prostate segmentation in MR images. MICCAI 2019.

  • Y. Wu, Y. Xia, Y. Song, D. Zhang, D. Liu, C. Zhang, and W. Cai. Vessel-Net: Retinal vessel segmentation under multi-path supervision. MICCAI 2019.

  • H. Jia, Y. Xia, Y. Song, D. Zhang, H. Huang, Y. Zhang, and W. Cai. 3D APA-Net: 3D adversarial pyramid anisotropic convolutional network for prostate segmentation in MR images. IEEE Transactions on Medical Imaging, 2019.

  • D. Liu, D. Zhang, Y. Song, F. Zhang, L. O'Donnell, and W. Cai. 3D large kernel anisotropic network for brain tumor segmentation. ICONIP 2018.

  • D. Zhang, Y. Song, D. Liu, H. Jia, S. Liu, Y. Xia, H. Huang, and W. Cai. Panoptic segmentation with an end-to-end cell R-CNN for pathology image analysis. MICCAI 2018.

  • Y. Wu, Y. Xia, Y. Song, Y. Zhang, and W. Cai. Multiscale network followed network model for retinal vessel segmentation. MICCAI 2018.

  • S. Liu, D. Zhang, Y. Song, H. Peng, and W. Cai. Automated 3-D neuron tracing with precise branch erasing and confidence controlled back tracking. IEEE Transactions on Medical Imaging, 2018.

  • Y. Xie, Y. Xia, J. Zhang, Y. Song, D. Feng, M. Fulham, and W. Cai. Knowledge-based collaborative deep learning for benign-malignant lung nodule classification on chest CT. IEEE Transactions on Medical Imaging, 2018.

  • A. Tareef, Y. Song, H. Huang, D. Feng, M. Chen, Y. Wang, and W. Cai. Multi-pass fast watershed for accurate segmentation of overlapping cervical cells. IEEE Transactions on Medical Imaging, 2018.

  • F. Zhang, W. Wu, L. Ning, G. McAnulty, D. Weber, B. Gagoski, K. Sarill, H. Hamoda, Y. Song, W. Cai, Y. Rathi, and L. O'Donnell. Suprathreshold fiber cluster statistics: Leveraging white matter geometry to enhance tractography statistical analysis. NeuroImage, 2018.

  • D. Zhang, S. Liu, Y. Song, D. Feng, H. Peng, and W. Cai. Automated 3D soma segmentation with morphological surface evolution for neuron reconstruction. Neuroinformatics, 2018.

  • Y. Song, F. Zhang, Q. Li, H. Huang, L. O'Donnell, and W. Cai. Locally-transferred Fisher vectors for texture classification. ICCV 2017.

  • Y. Song, Q. Li, H. Huang, D. Feng, M. Chen, and W. Cai. Low dimensional representation of Fisher vectors for microscopy image classification. IEEE Transactions on Medical Imaging, 2017.

  • Y. Song, Q. Li, F. Zhang, H. Huang, D. Feng, Y. Wang, M. Chen, and W. Cai. Dual discriminative local coding for tissue aging analysis. Medical Image Analysis, 2017.

  • F. Zhang, P. Savadjiev, W. Cai, Y. Song, Y. Rathi, B. Tunc, D. Parker, T. Kapur, R. Schultz, N. Makris, R. Verma, and L. O'Donnell. Whole brain white matter connectivity analysis using machine learning: An application to autism. NeuroImage, 2017.

  • Y. Song, W. Cai, H. Huang, D. Feng, Y. Wang, and M. Chen. Bioimage classification with subcategory discriminant transform of high dimensional visual descriptors. BMC Bioinformatics, 2016.

  • F. Zhang, Y. Song, W. Cai, S. Liu, S. Liu, S. Pujol, R. Kikinis, Y. Xia, M. Fulham, D. Feng, and ADNI. Pairwise latent semantic association for similarity computation in medical imaging. IEEE Transactions on Biomedical Engineering, 2016.

  • F. Zhang, Y. Song, W. Cai, A. Hauptmann, S. Liu, S. Pujol, R. Kikinis, M. Fulham, D. Feng, and M. Chen. Dictionary pruning with visual word significance for medical image retrieval. Neurocomputing, 2016.

  • Y. Song, W. Cai, Q. Li, F. Zhang, D. Feng, and H. Huang. Fusing subcategory probabilities for texture classification. CVPR 2015.

  • Y. Song, W. Cai, H. Huang, Y. Zhou, D. Feng, Y. Wang, M. Fulham, and M. Chen. Large margin local estimate with applications to medical image classification. IEEE Transactions on Medical Imaging, 2015.

  • Y. Song, W. Cai, H. Huang, Y. Zhou, Y. Wang, and D. Feng. Locality-constrained subcluster representation ensemble for lung image classification. Medical Image Analysis, 2015.

PhD Supervision

Current PhD Students (as primary or joint supervisor)

Donghao Zhang (2016.07 - )
Max Chu (2016.07 - )
Dongnan Liu (2017.10 - )
Veena Dodballapur (2017.10 - )
Priyanka Rana (2019.02 - )
Chaoyi Zhang (2019.02 - )
Yuqian Chen (2019.08 - )
Ari Tchetchenian (2020.02 - )
Jiayi Zhu (2020.05 - )

Graduated PhD Students (as joint supervisor)

Fan Zhang (now at Harvard University)
Afaf Tareef (now at Mutah University)
Siqi Liu (now at Siemens Healthineers, US)

Visiting PhD Students (current or graduated)

Haozhe Jia (from Northwestern Polytechnical University)
Yichen Wu (from Northwestern Polytechnical University)

Teaching

  • COMP9517: Computer Vision

  • COMP9417: Machine Learning and Data Mining

  • Honours and MIT projects supervision - interested students please email for topic discussion