Luping Zhou

PhD, IEEE Senior Member

Senior Lecturer & ARC DECRA Fellow

School of Computing and Information Technology
University of Wollongong, NSW 2522 Australia

Email: lupingz at uow.edu.au

Research Profile: ResearchGate     Google Scholar  

 

About

Dr. Luping Zhou is a Senior Lecturer in School of Computing and Information Technology, University of Wollongong, Australia. She obtained her PhD, MSc, and BEng from Australian National University, National University of Singapore and Southeast University, China, respectively. After PhD, she worked as a postdoctoral research fellow in University of North Carolina at Chapel Hill, USA and then a staff research scientist in Australian e-Health Research Centre, CSIRO. Zhou joined UOW in 2012 with “Vice Chancellor Research Fellowship”. She is a recipient of ARC DECRA (Discovery Early Career Researcher Award) award in 2015. Before she started her Ph.D, Zhou was a senior research engineer, developing medical imaging applications for surgical navigation and planning through virtual/augmented reality systems.

Zhou has broad research interest in medical image analysis, machine learning and computer vision. Her current research is focused on medical image analysis with statistical graphical models and deep learning.

Future Students

 

Motivated students who are interested in medical image analysis, machine learning and computer vision are encouraged to send email to lupingz at uow.edu.au to discuss potential research opportunities in these related fields.

 

China Scholarship Council (CSC) – UOW Joint Postgraduate Scholarships Program

The China Scholarship Council (CSC) and the University of Wollongong (UOW) are jointly offering postgraduate research scholarships to students from the People’s Republic of China who intend to undertake a postgraduate research degree at the University of Wollongong. UOW will provide an International Postgraduate Tuition Award (IPTA) to each student selected under this program.  This IPTA will pay the full tuition fees.

UOW may also accept students from Chinese University partner institutions for visiting research training programs whereby CSC students will be enrolled at the Chinese institution but will spend a component of their degree at UOW.

 

 

News

 

 

1. We are organizing a special issue onHigh Performance Computing in Bio-medical Informatics (HPC-BMI) with Neuroinformatics (Springer).  The online Call-for-Paper is available here. Paper submission period is May 1-31, 2017.

 

 

2. Our organising committee has successfully bid MICCAI 2019 in Hong Kong (General Chairs: Prof Dinggang Shen @ UNC-CH and Prof Tianming Liu @ UGA).

 

 

3. We are organizing a special issue “Machine Learning in Medical Imaging” with Pattern Recognition (Elsevier).  The online Call-for-Paper is available here. The submission is due on January 31, 2016, through the website here. Please select “SI:MLMI” for “Article Type” during the submission procedure.

 

 

4. Zhou received the early career award (DECRA 2016-2018) from Australian Research Council.

 

 

5. Zhou is in the list of MICCAI’15 Best Reviewers Runner-ups (14 in total over 700 Peer Reviewers).

 

 

6. Update: the workshop MICCAI-MLMI’15 has been completed successfully. This year, we again attracted above 140 registrants. The proceedings are available online here.

 

We are organizing the 6th international workshop on Machine Learning in Medical Imaging (MLMI 2015), held together with MICCAI 2015, in Munich, Germany. MLMI focuses on advancing the cutting-edge machine learning techniques and their use in medical imaging. The last workshop, MLMI 2014 held in Boston USA, attracted around 100 attendees, and the proceedings could be found here.

 

 

7. Zhou gave an invited talk on BrainKDD2015, hosted by ACM SIGKDD in Sydney in 2015.

 

Related Publications

(Note: ARC ERA2010 Ranking A*/A is highlighted in yellow)

 

2017

 

J22

W. Li, Y. Gao, L. Wang, L. Zhou, J. Huo, and Y. Shi, OPML: A One-Pass Closed-Form Solution for Online Metric Learning, Pattern Recognition (PR), 2017 accepted

J21

H. Ni, J. Qin, L. Zhou, Z. Zhao, J. Wang, and F. Hou,  Network Analysis in Detection of Early-stage Mild Cognitive Impairment, Physica A: Statistical Mechanics and its Applications, 2017 accepted

C28

L. Zhou, L. Wang, J. Zhang, Y. Shi and Y. Gao,  Revisiting Distance Metric Learning for SPD Matrix based Visual Representation, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR),  Hawaii, USA, 2017

C27

Z. Gao, L. Wang, L. Zhou, and M. Yang, Infomax Principle Based Pooling of Deep Convolutional Activations for Image Retrieval, IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, 2017

 

2016

 

J20

L. Zhou, L. Wang, L. Liu, P. Ogunbona, and D. Shen, Learning Discriminative Bayesian Networks from High-dimensional Continuous Neuroimaging Data, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), accepted. [Appendix]

J19

L. Wang, L. Liu, and L. Zhou, A Graph-embedding Approach to Hierarchical Visual Word Mergence, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS) 2016, accepted.

J18

J. Zhang, L. Zhou, and L. Wang, Subject-adaptive Integration of Multiple SICE Brain Networks with Different Sparsity, Pattern Recognition (PR), 2016, accepted.

J17

Z. Gao, L. Wang, L. Zhou and J. Zhang, HEp-2 Cell Image Classification with Deep Convolutional Neural Networks, IEEE Journal of Biomedical and Health Informatics (IEEE JBHI, originally IEEE T-ITB), 2016 (accepted in Jan 2016).

C26

Y. Zhao, L. Wang, I. Comor,  Z. Gao,  W. Zhang, and L. Zhou, Semi-supervised Weight Learning for the Spatial Search Method in ConvNet-based Image Retrieval,The International Conference on Digital Image Computing Techniques and Applications (DICTA), Gold Coast, Australia, 2016

C25

I. Comor, Y. Zhao,  Z. Gao, L. Zhou, and L. Wang,  Image Descriptors from ConvNets: Comparing Global Pooling Methods for Image Retrieval, The International Conference on Digital Image Computing Techniques and Applications (DICTA), Gold Coast, Australia, 2016

 

 

 

2015

 

B2

L. Zhou, L. Wang, Q. Wang, and Y. Shi (Eds.), Machine Learning in Medical Imaging6th international workshop, MLMI2015, Held in Conjunction with MICCAI 2015 in Munich, Germany, Proceedings,  Springer (ISBN: 978-3-319-24888-2), 2015

J16

H. Ni, L. Zhou, X. Ning, and L. Wang*, Exploring Multifractal-based Features for Mild Alzheimer’s Disease Classification, Magnetic Resonance in Medicine (MRM), 2015 (accepted in June 2015)

J15

J. Zhang, L. Wang, L. Zhou, and W. Li, Learning Discriminative Stein Kernel for SPD Matrices and Its Applications, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 2015 (accepted in May 2015)

J14

J. Zhang, L. Zhou, L. Wang, and W. Li,  Functional Brain Network Classification with Compact Representation of SICE Matrices, IEEE Transactions on Biomedical Engineering (T-BME), 2015 (accepted in Jan 2015)

 

J13

H. Ni, L. Zhou, P. Zeng, X. Huang, H. Liu, X. Ning,  Multifractal Analysis of White Matter Structural Changes on 3D Magnetic Resonance Imaging between Normal Ageing and Early Alzheimer’s Disease, Chinese Physics B (English Edition), 2015 (accepted in March 2015, SCI-indexed, IF 1.39)

C24

L. Wang, J. Zhang, L. Zhou, C. Tang, and W. Li, Beyond Covariance: Feature Representation with Nonlinear Kernel Matrices, International Conference on Computer Vision (ICCV), Santiago, Chile, 2015

 

 

2014

 

 

B1

G. Wu, D. Zhang, and L. Zhou (Eds.),  Machine Learning in Medical Imaging5th international workshop, MLMI2014, Held in Conjunction with MICCAI 2014 in Boston, USA, Proceedings,  Springer (ISBN: 978-3-319-10580-2), 2014

J12

X. Liu, L. Zhou, L. Wang, J. Zhang, J. Yin, and D. Shen, An Efficient Radius-incorporated MKL Algorithm for Alzheimer’s Disease Prediction, Pattern Recognition (PR), 2014 (accepted in Dec 2014)

C23

L. Zhou, L. Wang, and P. Ogunbona, Discriminative Sparse Inverse Covariance Matrix: Application in Brain Functional Network Classification, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Ohio, USA, 2014

 

C22

L. Zhou, L. Wang, L. Liu, P. Ogunbona, and D. Shen, Max-margin Based Learning for Discriminative Bayesian Network from Neuroimaging Data, International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Boston, USA, 2014

 

C21

J. Zhang, L. Zhou, L. Wang, and W. Li, Exploring Compact Representation of SICE Matrices for Functional Brain Network Classification, MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), Boston, USA, 2014

C20

Z. Gao, J. Zhang, L. Zhou and L. Wang, HEp-2 Cell Image Classification with Convolutional Neural Networks,  Contest on Pattern Recognition Techniques for Indirect Immunofluorescence Images Analysis in International Conference on Pattern Recognition (ICPR), Sweden, 2014 (invited paper)

C19

Y. Zhao, Z. Gao, L. Wang and L. Zhou, Experimental  Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering, The International Conference on Digital Image Computing: Techniques and Applications (DICTA), Wollongong, Australia, 2014

CA6

V. Doré, P. Bourgeat, L. Zhou, J. Fripp, R. Martins, L. Macaulay, D. Ames, C. L. Masters, B. Brown, C. C. Rowe, O. Salvado, and V. L. Villemagne. Automated Reporting of Amyloid PET Quantification on Brain Surface through a Web Interface, In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Copenhagen, Denmark, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2014

 

 

 

2013

 

 

BC3

L. Zhou, L. Wang, L. Liu, P. Ogunbona and D. Shen, Support Vector Machines for Neuroimage Analysis: Interpretation from Discrimination. Support Vector Machines Applications, Springer (ISBN: 978-3-319-02300-7), 2013

BC2

L. Wang, L. Liu, L. Zhou and K.L. Chan, Application of SVMs to the Bag-of-features Model – A Kernel Perspective. Support Vector Machines Applications, Springer  (ISBN: 978-3-319-02300-7), 2013

J11

L. Wang, L. Zhou, C. Shen, L. Liu and H. Liu, A Hierarchical Word-merging Algorithm with Class Separability Measure, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2013 (accepted in August, 2013)

J10

L. Zhou, O. Salvado, V. Dore, P. Bourgeat, P. Raniga, S. L. Macaulay, D. Ames, C. L. Masters, K. A. Ellis, V. L. Villemagne, C. C. Rowe, and J. Fripp, MR-less Surface-based Amyloid Assessment based on 11C PiB PET, PLoS One, 2013 (accepted in Novermber, 2013)

 

J9

V. Dore, V. L. Villemagne, P. Bourgeat, J. Fripp, O. Acosta, G. Chetelat, L. Zhou, R. Martins, K. Ellis, C. L. Masters, D. Ames, , O. Salvado, and C. C. Rowe. Cross-sectional and Longitudinal Analysis of the Relationship between Aβ Deposition, Cortical Thickness and Memory in Cognitively Unimpaired Individuals and Alzheimer’s Disease,  JAMA Neurology 2013;70(7):903-911

J8

F. Liu, L. Zhou, C. Shen, J. Yin. Multiple Kernel Learning in the Primal for Multi-modal Alzheimer’s Disease Classification, IEEE Journal on Biomedical and Health Informatics (originally IEEE Trans on Information Technology in Biomedicine), 2013

C18

L. Zhou, L. Wang, L. Liu, P. Ogunbona, and D. Shen, Discriminative Brain Effective Connectivity Analysis for Alzheimers Disease: A Kernel Learning Approach upon Sparse Gaussian Bayesian Network, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Oregon, USA, 2013

C17

L. Wang, J. Zhang, L. Zhou, and W. Li, A Fast Approximate AIB Algorithm for Distributional Word Clustering, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Oregon, USA, 2013

C16

J. Zhang, L. Wang, L. Liu, L. Zhou, W. Li. Accelerating the Divisive Information-Theoretic Clustering of Visual Words, In International Conference on Digital Image Computing Techniques and Applications (DICTA), Tasmania, Australia, 2013

CA5

V. Dore, P. Bourgeat, L. Zhou, J. Fripp, R. Martins, L. Macaulay, C. Masters, D. Ames, K.A. Ellis, C. Rowe, O. Salvado, and V. Villemagne. MR-less Cortical Surface-projection of PET Scans with 11C and 18F Labeled Radiotracers, In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Boston, USA & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2013

 

2012

 

 

C15

L. Zhou, O. Salvado, V. Dore, P. Bourgeat, P. Raniga, V. L. Villemagne, C. C. Rowe, and J. Fripp, MR-less Surface-based Amyloid Estimation by Subject-specific Atlas Selection and Bayesian Fusion, In Proc. International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), France, October 2012 

C14

P. Bourgeat, P. Raniga, V. Dore, L. Zhou, S.L. Macaulay, R. Martins, C. Masters, D. Ames, K. A. Ellis, V. Villemagne, C. Rowe, O. Salvado, and J. Fripp. Manifold Driven MR-less PiB SUVR Normalisation,  In MICCAI 2012 Workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders (NIBAD'12), Nice, France, October 2012.

CA4

L. Zhou, V. Dore, J. Fripp, P. Bourgeat ,P. Raniga, R. Martins, L. Macaulay, C. Masters, D. Ames, K. A. Ellis, V. Villemagne, C. Rowe, O. Salvado, and AIBL research group. MRI-independent Automated Surface-projection of Amyloid Imaging Scans, In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012

 

CA3

P. Bourgeat, J. Fripp, P. Raniga, V. Dore, L. Zhou, R. Martins, L. Macaulay, C. Masters, D. Ames, K.A. Ellis, V. Villemagne, C. Rowe, O. Salvado, and AIBL research group, Longitudinal Modeling of Joint PiB/MRI Changes in Alzheimer’s Disease, In Alzheimer's Association International Conference in Alzheimer's Disease 2012, Vancouver (AAIC), Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012

 

CA2

P. Bourgeat, O. Salvado, P. Raniga, V. Dore, L. Zhou, R. Martins, L. Macaulay, C. Masters, D. Ames, K. A. Ellis, V. Villemagne, C. Rowe,J. Fripp, and AIBL research group, Classification of Alzheimer’s subject based on PiB-MR Manifold learning,  In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012.

 

CA1

V. Dore, J. Fripp, P. Bourgeat, O. Acosta, L. Zhou, P. Raniga, R. Martins, L. Macaulay, K. Ellis, C. Masters, D. Ames, V. Villemagne, C. Rowe, O. Salvado and AIBL research group, Longitudinal Analysis of Cortical Thickness in PiB+ and PiB- Healthy Elderly Controls, In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC) Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012.

 

 

2011

 

 

 

BC1

C.Y. Wee*, D. Zhang*, L. Zhou*, P.T. Yap, and D. Shen. Machine Learning Techniques for AD/MCI Diagnosis and Prognosis (invited book chapter). Machine Learning in Healthcare Informatics, Springer, 2011. (* equally contribute)

 

J7

L. Zhou, Y. Wang, Y. Li, P.T. Yap, and D. Shen, Hierarchical Anatomical Brain Networks for MCI Prediction: Revisiting Volumetric Measures, accepted by PLoS One, 2011.

.

J6

D. Zhang, Y. Wang, L. Zhou, H. Yuan, and D. Shen, Multimodal Classification of Alzheimer's Disease and Mild Cognitive Impairment, accepted by NeuroImage, 2011. 

 

J5

Y. Li, Y. Wang, G. Wu, F. Shi, L. Zhou, W. Lin, and D. Shen, Discriminant Analysis of Longitudinal Cortical Thickness Changes in Alzheimer's Disease Using Dynamic and Network Features, accepted by Neurobiology of Aging, 2011. 

 

C13

L. Zhou, Y. Wang, Y. Li, P.T. Yap, and D. Shen, Hierarchical Anatomical Brain Networks for MCI Prediction by Partial Least Square Analysis, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 11), Colorado Springs, USA, June 21-23, 2011.

 

C12

L. Zhou, S. Liao, W. Li, and D. Shen, Learning-based Prostate Localization for Image Guided Radiation Therapy (invited paper), In IEEE International Symposium on Biomedical Imaging (ISBI), Chicago, USA, March 30 - April 2, 2011. 

 

C11

L. Zhou and O. Salvado, A Comparison Study of Ellipsoid Fitting for Pose Normalization of Hippocampal Shapes, In Proceedings of International Conference on Digital Image Computing: Techniques and Applications (DICTA), Brisbane, Australia, December 2011.

 

 

2010

 

 

J4

L. Zhou, L. Wang, and C. Shen, Feature Selection with Redundancy-constrained Class Separability, IEEE Transactions on Neural Networks 21(5):853-858, 2010.

 

C10

L. Zhou, L. Wang, C. Shen, and N. Barnes, Hippocampal Shape Classification Using Redundancy Constrained Feature Selection, In International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI) 2010: 266-273 2010.  (MICCAI Travel Award)

 

2009

 

 

J3

L. Zhou, R. Hartley, L. Wang, P. Lieby and N. Barnes, Identifying Anatomical Shape Difference by Regularized Discriminative Direction, IEEE Transactions on Medical Imaging 28(6): 937-950 2009.

 

J2

L. Zhou, P. Lieby, N. Barnes, C. Reglade-Meslin, J. Walker, N. Cherbuin, and R. Hartley, Hippocampal Shape Analysis for Alzheimer’s Disease Using an Efficient Hypothesis Test and Regularized Discriminative Deformation, Hippocampus, 19(6), June 2009, pp533-540, 2009. (Impact Factor: 5.176)

 

C9

Q. Shi, L. Zhou, L. Cheng, and D. Schuurmans, Discriminative Maximum Margin Image Object Categorization with Exact Inference,, International Conference on Image and Graphics, September, Xi'An China, 2009.

 

2008

 

 

C8

L. Zhou, R. Hartley, L. Wang, P. Lieby, and N. Barnes Regularized Discriminative Direction for Shape Difference Analysis,, In International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI) 2008: 628-635, 2008. 

 

C7

L. Wang, L. Zhou, and C. Shen, A Fast Algorithm for Creating a Compact and Discriminative Visual Codebook, European Conference on Computer Vision (ECCV) 2008: 719-732 2008.

 

J1

L. Wang, K.L. Chan, P. Xue, and L. Zhou, A Kernel-Induced Space Selection Approach to Model Selection in KLDA, IEEE Transactions on Neural Networks 19(12): 2116-2131 2008.

 

 

2007

 

 

C6

L. Zhou, R. Hartley, P. Lieby, N. Barnes, K. Anstey, N. Cherbuin, and P. Sachdev, A Study of Hippocampal Shape Difference Between Genders by Efficient Hypothesis Test and Discriminative Deformation,, In International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI) 2007: 375-383, 2007. 

 

 

Before 2006

 

 

 

C5

L. Zhou, Y. Wang, C. Goh,, R.A. Kockro and L. Serra, Stereoscopic Visualization and Editing of Automatic Abdominal Aortic Aneurysms (AAA) Measurements for Stent Graft Planning,, In Proceedings of SPIE’s Electronic Imaging, USA, January 2006, pp57-65,, 2006

 

C4

R.A. Kockro, X. Liang, C. Goh, L. Zhou, C. Zhu, TT Yeo, and L. Serra, DexRay: An Augmented Reality Surgical Navigation System, In Conference of European Association of Neurosurgical Societies (EANS), Portugal, September, 2003.

 

C3

L. Zhou, I. Atmosukarto, W.K. Leow, and Z. Huang, Reconstruting Surface Discontinuities by Intersecting Tangent Planes of Advancing Mesh Frontiers, In Proc. Computer Graphics International (CGI), UK, July 2002, pp183-199,, 2002.

 

C2

I. Atmosukarto, L. Zhou, W.K. Leow, and Z. Huang, Polygonizing Nonuniformly Distributed 3D Points by Advancing Mesh Frontier, In Proc. Computer Graphics International (CGI), Hong Kong, July 2001, pp175-182,, 2001.

 

C1

W.K. Leow, Z. Huang, L. Zhou, I. Atmosukarto, and Y. Zhang, Acquiring 3D Models from Images for Multimedia Systems, In Proc. Multimedia Modeling (MMM), Japan, November 2000, pp439-449,, 2000.

 

 

 

Patents

1

W.K. Leow, Z. Huang, L. Zhou, and I. Atmosukarto, Frontier Advancing Polygonization, US7091969, granted on 15 Aug 2006, Licensed 2010.

2

L. Zhou, Y. Wang, and L.C. Goh, A Method for Measuring Tube-like Organs Using Knowledge Structure Mapping, WIPO patent application WO/2006/056613, US patent application No. 11/289230 (pending).

3

L. Zhou, L. Serra, and L.C. Goh, Systems and Methods for Collaborative Interactive Visualization of 3D Data Sets over a Network, WIPO patent application WO/2007/108776, US patent application No. 11/649425 (pending).

4

R. Hartley, and L. Zhou, Shape Discrimination, WIPO patent application WO/2009/052581, (pending).

 

5

S. Liao, D. Shen and L. Zhou, Learning-based Prostate Localization for Image Guided Radiation Therapy,  Application filed 2011, Assignee: University of North Carolina at Chapel Hill, USA

6

L. Zhou, J. Fripp, O. Salvado, etc. MRI-independent amyloid assessment, Application filed Dec. 2011, Assignee: CSIRO, Australia

 

 

Student Supervision

[Ongoing]

 

Biting Yu: PhD, University of Wollongong (Primary Supervisor)

Topic: “Deep Learning Techniques for Medical Image Analysis”

 

Zhimin Gao: PhD, University of Wollongong (Supervision Panel)

Topic:“Developing Advanced Deep Learning Models for Visual Recognition”

 

Yan Zhao: PhD, University of Wollongong (Supervision Panel)

Topic:“Deep Learning: Theories and Applications”

 

Melih Engin: MPhil, University of Wollongong (Co-supervisor)

Topic: “Deep Learning Techniques for Image Retrieval”

 

[Complete]

 

Jianjia Zhang: PhD, University of Wollongong (Supervision Panel)

Topic:  Medical Image Analysis with Advanced Visual Recognition Models”

(PhD granted, now post-doc fellow at Data61, Sydney)

 

Huangjing Ni: Visiting PhD, (complete, Co-supervisor)

Topic: “Exploring Multifractal-based features for the Diagnosis of Alzheimer’s Disease”

(now post-doc fellow at Brainnetome Center, Institute of Automation, Chinese Academy of Sciences)

 

Gentian Li: Visiting Undergraduate (complete, advisor)

Topic: “Reconstructing Tractography from Brain Diffusion Tensor Imaging (DTI) for Neuroimage Analysis”

 

Teaching

Subject Coordinator & Lecturer: CSIT121/821 Object Oriented Design & Programming (Java), UOW, Autumn Session 2017

Subject Coordinator & Lecturer: CSCI446/946 Multimedia Content Management, UOW, Spring Session 2016

Subject Coordinator & Lecturer: CSCI433/933 Pattern Recognition, UOW, Autumn Session 2016

Subject Coordinator & Lecturer: CSCI103 Algorithms and Problem Solving, UOW, Spring Session 2015

Guest Lecturer: CSCI336 Computer Graphics, UOW, 2014 (OpenGL and GLUT programming)

Guest Lecturer: CSCI446/946 Multimedia Content Management, UOW, 2014 (Shape Descriptor)

Guest Lecturer: CSCI336 Computer Graphics, UOW, 2013 (OpenGL and GLUT programming)

 

Administrative Duties

APD (Academic Program Director) of Master of Computer Science in CCNU-UOW joint institute

One of the three APDs of Master of Computer Science in SCIT, UOW

 

Research Activities

Guest editor for the special issue on High Performance Computing in Bio-medical Informatics (HPC-BMI) with Neuroinformatics (Springer), 2017.

Organising committee of MICCAI 2019,  Hongkong, 2019

Succeeded in DECRA (Discovery Early Career Researcher Award) 2016-2018 from ARC (Australian Research Council)

Listed in MICCAI’15 Best Reviewers Runner-ups (14 in total over 700 Peer Reviewers), Munich, Germany, MICCAI 2015

Guest editor for special issue “Machine Learning in Medical Imaging” with Pattern Recognition (Elsevier), 2015-2016

Invited talk at BrainKDD2015 (Data Mining for Brain Science), hosted by ACM SIGKDD, Sydney, Australia, Aug. 2015

Co-chair MICCAI15 workshop MLMI2015 (Machine Learning in Medical Imaging), Munich, Germany, Oct. 2015

Co-chair MICCAI14 workshop MLMI 2014 (Machine Learning in Medical Imaging), Boston,  USA,  Sep. 2014

Co-chair ICDM14 workshop DMMI2014 (Data Mining in Medical Imaging), Shenzhen, China, Dec. 2014.

Serve DICTA 2014 as the publicity chair, Wollongong, Australia, Dec. 2014

Program Committee: MICCAI-MLMI (Machine Learning in Medical Imaging) 2011-2016, MICCAI-CMMI (Computational Methods for Molecular Imaging) 2014-2015, MICCAI-MCV (Medical Computer Vision) 2015-2016, BrainKDD 2016, ICIG 2015, PSIVT 2013, ISNN2010

 

Grant Reviewer:

Nov Project, Breast Cancer Now, UK, 2016

Discovery Project, Australian Research Council (ARC), Australia, 2016

DECRA, Australian Research Council (ARC), Australia, 2016

Biomedical Junior Fellowship, Alzheimer’s Society, UK, 2016

ASDI research proposal, the Netherlands e-Science Center (NLeSC) and the Netherlands Organisation for Scientific Research (NWO), 2015

“Memorable” programme, The Netherlands Organisation for Health Research and Development (ZonMw) and the National Initiative Brain & Cognition (NIHC), 2014

 

Paper Reviewer: IEEE Trans. on Medical Imaging (TMI), IEEE Trans. on Biomedical Engineering (TBME), IEEE Journal on Biomedical and Health Informatics (JBHI), IEEE Trans. on Computational Biology and Bioinformatics (TCBB), Computerized Medical Imaging and Graphics (CMIG), Machine Vision and Application (MVA), Information Sciences, IEEE Trans on Circuits and Systems for Video Technology (TCSVT), Pattern Recognition, Neuroimage, PLoS One, Human Brain Mapping, Brain Connectivity, Cognitive Computation, Scientific Report, BMC Bioinformatics, MICCAI 2010-2016, AAAI 2015, MLMI 2011-2015, etc.

 

Visit / Talk @:

Australian e-Health Research Centre, CSIRO, Brisbane, Australia, 2016

Faculty of Engineering, Architecture and Information Technology, University of Queensland,  Australia, 2016

School of Biomedical Engineering, Zhejiang University, China, 2016

School of Computer Science and Technology, Nanjing Normal University, China, 2015

Department of Computer Science, Nanjing University of Aeronautics and Astronautics, China, 2015

State Key Laboratory for Novel Software Technology, Nanjing University, China, 2015

Wollongong Hospital, NSW, Australia, 2015

Biomedical & Multimedia Information Technology (BMIT) Research Group, University of Sydney, Australia, 2015

Biodesign Institute and Data Mining Machine Learning Lab, Arizona State University, USA, 2013

Machine Learning and Cognition Lab, Nanjing Normal University, China, 2013

Department of Computer Science, Nanjing University of Aeronautics and Astronautics, China, 2013

School of Computer, National University of Defence Technology, China, 2013

The Affiliated Sixth People’s Hospital, Shanghai Jiaotong University, China, 2013

Jiangsu Provincial People’s Hospital, Nanjing, China, 2013

Advanced Analytics Institute, University of Technology Sydney, Australia, 2013

Illawarra Health and Medical Research Institute, University of Wollongong, Australia, 2012

Austin Hospital, Melbourne, Australia, 2011, 2012

Australian e-Health Research Centre, Brisbane, Australia, 2009

Chair for Computer Aided Medical Procedures & Augmented Reality (CAMP), Technical University of Munich, Germany, June~August 2009