ZongYuan Ge 戈宗元

Senior Research Fellow at Monash University | Deep Learning Specialist at NVIDIA

z dot ge at outlook.com or zongyuan.ge at monash.edu

Previous:

IBM Research, Melbourne, VIC, Australia. 2016-2018

DeepGlint, Beijing, China. 2015-2016

ACRV, Brisbane, QLD, Australia. 2013-2016

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

ZongYuan Ge, is currently a Senior Research Fellow at Monash and also serve as a Deep Learning Specialist at NVIDIA East Asia Research Centre. Before he joined Monash Zongyuan was a research scientist at IBM Research Australia doing research in medical AI during 2016-2018.

He has been awarded science accomplishment award and manger choice of the year inside IBM for his excellent contributions to those projects. In 2017, Zongyuan was selected as one of the 200 Most Qualified Young Researchers in Computer and Mathematics by the Scientific Committee of the Heidelberg Laureate Forum Foundation in 2017.

Formerly Zongyuan 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. He has enthusiasm for AI, computer vision , medical image, robotics and deep learning research.

News

  • Attending ICRA 2018
  • One JAMA paper submitted
  • 3 MICCAI 2018 papers submitted
  • IBM 2017 Science Accomplishment Award
  • Assigned as ACRV research affiliate
  • 3 MICCAI 2017 papers accepted from our group
  • 1 WMC 2017 paper accepted as oral presentation and there will be a IBM booth
  • 1 BMVC 2017 paper about using GAN for OpenSet accepted

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] [pdf]

Artificial intelligence offers improved availability and standardisation for melanoma screening of populations, World Melanoma Congress (WMC), 2017 [oral] https://www.ibm.com/cognitive/au-en/melanoma/

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]

Robotic 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:

  • Transactions on Medical Imaging (TMI): 2018
  • Medical Imaging Computing and Computer Assisted Intervention (MICCAI): 2017 2018
  • International Joint Conference on Artificial Intelligence (IJCAI): 2017
  • IEEE Winter Conference on Applications of Computer Vision (WACV): 2017 2018
  • 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
  • Journal of Biomedical and Health Informatics

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).