ZongYuan Ge 戈宗元

Research Scientist

z dot ge at outlook.com & zongyuan at au1 dot ibm dot com

IBM Research, Melbourne, VIC, Australia. 2016-Now

DeepGlint, Beijing, China. 2015-2016

ACRV, Brisbane, QLD, Australia. 2013-2016

Book: Computational and Statistical Methods for Analysing Big Data with Applications

My name is ZongYuan Ge, I joined IBM Research in May 2016 as a postdoctoral research position. Formerly I was a PhD candidate with Australian Centre for Robotics Vision at Queensland University of Tech and worked with Prof. Peter Corke, Dr. Chris McCool and Dr. Conrad Sanderson. I have enthusiasm for AI, computer vision , medical image, robotics and deep learning research.

I and colleagues are currently developing skin disease detection applications. Press is here: https://www.ibm.com/cognitive/au-en/melanoma/

If you found anything interested, got any questions, visiting chance, internship at IBM or simply would like to have a general chat, please feel free to contact me. Even though due to IBM policy some codes are not allowed to distribute, but I will do my best to help re-produce the methods.


  • 3 MICCAI 2017 papers accepted from our group
  • 1 WMC paper accepted as oral presentation and there will be a IBM booth
  • 1 BMVC 2017 paper about GAN accepted
  • We are hiring interns!! Send me a email if you are interested.
  • TJ. Watson Lab visiting confirmed.

Medical Imaging Research

ZongYuan. Ge, S.Demyanov, R.Chakravorty, R.Garnavi, Skin disease recognition using deep saliency features and multimodal learning of dermoscopy and clinical images, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017 [poster]

Artificial intelligence offers improved availability and standardisation for melanoma screening of populations, World Melanoma Congress (WMC), 2017 [oral]

ZongYuan. Ge, S.Demyanov, S.Bozorgtabar, R.Chakravorty, M.Abedini, R.Garnavi, Exploiting local and generic features for accurate skin lesions classification using clinical and dermoscopy imaging, IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, 2017 [paper] [poster]

S.Bozorgtabar, ZongYuan. Ge, R.Chakravorty, M.Abedini, S.Demyanov, R.Garnavi, Investigating deep side layers for skin lesion segmentation, IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, 2017 [paper]

S.Demyanov, R.Chakravorty, ZongYuan. Ge, S.Bozorgtabar, R.Garnavi, A.Halpern, Tree-Loss function for training neural networks on weakly-labeled datasets, IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, 2017 [paper]

Fine-Grained Research

ZongYuan. Ge, C.Mccool, C.Sanderson, P.Wang, L.Liu, I.Reid, P.Corke, Exploiting temporal Information for fine-grained classification, DICTA, Gold Coast, Australia, 2016. (APRS Best Paper Award) [paper] [dataset] [slides]

ZongYuan. Ge, A.Bewley, C. McCool, C. Sanderson, B.Upcroft, and P. Corke, Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks in, IEEE Winter Conference on Applications of Computer Vision (WACV), 2016. [paper] [code] [poster]

ZongYuan. Ge, C. McCool, C. Sanderson, and P. Corke, Subset Feature Learning for Fine-Grained Category Classification, in Proc. Int. Conf. Proceeding of Computer Vision and Pattern Recognition (CVPR) Deep Vision, Boston, 2015. [paper] [poster]

ZongYuan. Ge, C. McCool, C. Sanderson, and P. Corke, Content Specific Feature Learning for Fine-Grained Plant Classification. in Proc.Conf and Labs of Evaluation Forum (CLEF), working notes, Toulouse, France, 2015. (First Runner-up in the competition) [paper]

ZongYuan. Ge, C. McCool, C. Sanderson, A. Bewley, Z. Chen, and P. Corke, Fine-Grained Bird Species Recognition via Hierarchical Subset Learning, in Proc.Int.Conf. Image Processing (ICIP), Quebec City, Canada, 2015. [paper] [poster]

ZongYuan. Ge, C. McCool, C. Sanderson, and P. Corke, Modelling Local Deep Convolutional Neural Network Features to Improve Fine-Grained Image Classification, in Proc.Int.Conf. Image Processing (ICIP), Quebec City, Canada, 2015. [paper] [poster]

K. Anatharajah, ZongYuan. Ge, C. McCool, S. Denman, C. Fookes, P. Corke, D. Tjondronegoro, and S. Sridharan, Local Inter-Session Variability Modelling for Object Classification, in Proc.Int. IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs CO, 2014. [paper] [poster]

Robotics Vision Research

H.LU, Y.Li, T.Uemura, ZongYuan.Ge, Hyoungseop Kim, FDCNet: filtering deep convolutional network for marine organism classification, Multimedia Tools and Applications, 2017. [paper]

L.Wu, Y.Wang, ZongYuan. Ge, Structured Deep Hashing with Convolutional Neural Networks for Large-scale Person Re-identificaiton, Computer Vision and Image Understanding (CVIU), 2017. [paper]

I.Sa, ZongYuan. Ge, F.Dayoub, B. Upcroft, T.Perez, C.Mccool, DeepCrops: Rapid training and deployment of multi-modal crop detection for agricultural robotics application, Sensors, 2016. [paper]

A.Bewley, ZongYuan. Ge, L.Ott, F.ramos, B.Upcroft, Simple Online and Realtime Tracking, Int.Conf. Image Processing (ICIP), Arizona, USA, 2016. [paper]

Z.Chen, S.Lowry, A.Jacobson, ZongYuan. Ge, M.Milford, Distance Metric Learning for Feature-Agnostic Place Recognition, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015. [paper]

General Computer Vision Research

ZongYuan Ge, S.Demyanov, Z.Chen, R.Garnavi, Generative OpenMax for Multi-Class Open Set Classification, British Machine Vision Conference (BMVC), 2017. [paper]

Professional Service

Reviewer for:

  • International Joint Conference on Artificial Intelligence (IJCAI): 2017
  • IEEE Winter Conference on Applications of Computer Vision (WACV): 2017
  • IEEE International Symposium on Biomedical Imaging (ISBI): 2017
  • International Conference on Digital Image Computing: Techniques and Applications (DICTA): 2017
  • IEEE Transactions on Image Processing (TIP)
  • IEEE Transaction on Multimedia (ToM)
  • ELSEVIER Computers & Electrical Engineering
  • International Journal of Applied Mathematics and Computer Science (AMCS)
  • IBM Journal of Research and Development

Mentors (Friends) and Colleagues

Chris Mccool (ACRV); Peter Corke (ACRV); Conrad Sanderson (Data61); Chunhua Shen (Uni Adelaide); Ian Reid (Uni Adelaide); Yongshen Gao (Griffith Uni); Jun Zhou (Griffith Uni); Xuming He (ShanghaiTech); Le Lu (NIH); Yong Zhao (DeepGlint).