Doctor Yi Guo

Dr Guo, Yi

Data Science, Computational Statistics and Machine Learning
Centre for Research in Mathematics and Data Science

Biography

Yi Guo received the B. Eng. (Hons.) in instrumentation in 1998, and the M. Eng. in automatic control in 2002. From 2005, he studied Computer Science at the University of New England, Armidale, Australia, focusing on di- mensionality reduction for structured data with no vectorial representation. He received a Ph.D. degree in 2008. Between 2008 and 2016, he was with CSIRO, working as a computational statistician on various projects in spectroscopy, remote sensing and materials science. He recently joined Center for Research in Mathematics at the School of Computing, Engineering and Mathematics, Western Sydney University. 

Qualifications

  • PhD University of New England

Professional Memberships

  • IEEE member (2016 - 2017)

Organisational Unit (School / Division)

  • Mathematics

Contact

Email: y.guo@westernsydney.edu.au
Phone: (02) 9685 9374
Location: EN.1.35
Parramatta

Teaching

Current Teaching Areas

  • 301034 Predictive Modeling
  • 301117 Predictive Analytics
  • 301111 Discovery Project
  • 300597,300598 Master Project 1&2
  • Under development, Optimisation

Publications & Code

Scholary books and chapters

  • Kaitao Lai, Natalie Twine, Aidan O’brien, Yi Guo, Denis Bauer. Artificial Intelligence and Machine Learning in Bioinformatics, Reference Module in Life Sciences, 2018, ISBN: 978-0-12-809633-8
  • Yi Guo, Hongdong Li, Weidong Cai, Manzur Murshed, Zhiyong Wang, Junbing Gao, David Dagan Feng. Proceedings of International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE Catalog Number: CFP17397-ART, ISBN: 978-1-5386-2839-3, 2017
  • Feng Li, Yi Guo. An Introduction to Compressive Sensing. Science Press, 2015 (in Chinese)

Journal Articles

  • Yi Guo, Stephen Tierney, Junbin Gao, Robust Functional Manifold Clustering, IEEE Transactions on Neural Networks and Learning Systems, 2020 [pdf][code]
  • Kingshuk Mazumdar, Dongmo Zhang, Yi Guo, Portfolio selection and unsystematic risk optimisation using swarm intelligence, Journal of Banking and Financial Technology, 2019
  • Junjie Yang, Yi Guo, Zuyang Yang, Liu Yang, Shengli Xie, Estimating Number of Speakers via Density-Based Clustering and Classification Decision, IEEE Access, Vol 7, 2019[pdf][code]
  • Junjie Yang, Yi Guo, Zuyang Yang, Member, Shengli Xie, Under-determined Convolutive Blind Source Separation Combining Density-based Clustering and Sparse Reconstruction in Time-Frequency Domain, IEEE Transactions on Circuits and Systems I, 2019[pdf][code]
  • Yang Liu, Yi Guo, Feng Li, Lei Xin, Puming Huang, Sparse Dictionary Learning for Blind Hyperspectral Unmixing, IEEE Geoscience and Remote Sensing Letters, 2018[pdf]
  • Ming Yin, Junbin Gao, Shengli Xie,Yi Guo, Multi-view Subspace Clustering via Tensorial t-Product Representation, IEEE Transactions on Neural Networks and Learning Systems, 2018[pdf]
  • Mark Berman, Zhipeng Hao, Glenn Stone and Yi Guo, An investigation into the impact of band error variance estimation on intrinsic dimension estimation in hyperspectral images, IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, 2018[pdf]
  • Yi Guo, Feng Li, Peter Caccetta, Drew Devereux, Multiple Temporal Mosaicing for Landsat TM Satellite Images, Journal of Applied Remote Sensing, 2017
  • Feng Li, Lei Xin, Yi Guo, Xianghao Kong, Xiuping Jia, Super Resolution for GaoFen-4 Remote Sensing Images, IEEE Geoscience And Remote Sensing Letters, 2017
  • Anthony Traylen, Peter Caccetta, Yi Guo, Mark Berman, Ian C. Lau, Endmember Search And Proportion Estimates From Airborne Hyperspectral Surveys, Internatinal Journal of Remote Sensing, 2017
  • Xia Hong, Sheng Chen, Yi Guo, Junbin Gao, L1 Norm Penalized Orthogonal Forward Regression”, International Journal of Systems Sciences, 2017
  • Mark Berman, Leanne Bischof, Ryan Lagerstron, Yi Guo, Jon Huntington, Peter Mason and Andrew A. Green, A Comparison Between Three Sparse Unmixing Algorithms Using a Large Library of Shortwave Infrared Mineral Spectra, IEEE Transactions on Geoscience and Remote Sensing 2017
  • Feng Li, Xin Lei, Yi Guo, Junbin Gao, Xiuping Jia, A Framework of Mixed Sparse Representations for Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing 2016
  • Zhipeng hao, Mark Berman, Yi Guo, Glenn Stone, Iain Johnstone. Semi-Realistic Simulations of Natural Hyperspectral Scenes, IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing 2016
  • Yongguang Zhai , Lifu Zhang , Nan Wang , Yi Guo , Yi Cen , Taixia Wu , Qing-Xi Tong. A Modified Locality-Preserving Projection Approach for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, 2016
  • Aidan R. O’Brien, Neil F. W. Sanders, Yi Guo, Fabian A. Buske, Rodney J. Scott, Denis C. Bauer. VariantSpark: Population Scale Clustering of Genotype Infromation, BMC Genomics, 2016
  • David Clifford, Yi Guo. Combining two soil property rasters using an adaptive gating approach. Soil Research, 2015
  • Ming Yin, Junbin Gao, Zhouchen Lin, Qinfeng Shi, Yi Guo. Dual Graph Regularized Low-rank Matrix Approximation for Data Representation, IEEE Transactions on Image Processing 2015
  • Ming Yin, Junbin Gao, Yi Guo. A Nonlinear Low-rank Representation on Stiefel Manifold, Electronics Letters, 2015
  • Yi Guo, Junbin Gao, Feng Li. Random Spatial Subspace Clustering. Knowledge-Based Systems, 2014
  • Yi Guo, Mark Berman and Junbin Gao. Group Subset Selection for Linear Regression. Computational Statistics and Data Analysis, 2014
  • Yi Guo, Junbin Gao, Feng Li. Spatial Subspace Clustering for Drill Hole Spectral Data, Journal of Applied Remote Sensing, 2014
  • Xuejian Sun, Lifu Zhang, Hang Yang, Taixia Wu, Yi Cen, and Yi Guo, Enhancement of Spectral Resolution for Remotely Sensed Multispectral Image. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014
  • Feng Li, ChuanRong Li, LingLi Tang, Yi Guo. Elastic registration for airborne multispectral line scanners, Journal of Applied Remote Sensing, 2014
  • Yi Guo and Mark Berman. A Comparison Between Subset Selection and L1 Regularisation with An Application in Spectroscopy. Journal of Chemometrics and Intelligent Laboratory Systems, 2012
  • Paul W. Kwan, Junbin Gao, Yi Guo, Keisuke Kameyama. A Learning Framework for Adaptive Fingerprint Identification using Relevance Feedback. International Journal of Pattern Recognition and Artificial Intelligence, 2010
  • Junbin Gao, Paul W. Kwan, Yi Guo. Robust Multivariate L1 Principal Component Analysis and Its Application in Dimensionality Reduction. Neurocomputing, 2009, Vol 72, 1242-1249
  • Yi Guo, Junbin Gao, Paul W. Kwan. Twin Kernel Embedding. IEEE Transaction on Pattern Analysis and Machine Intelligence. 2008, Vol 30, No. 8, 1490-1495
  • Yi Guo, Junbin Gao, Paul W. Kwan. Visualization of Protein Structure Relationships Using Constrained Twin Kernel Embedding. International Journal of Biomedical Science and Engineering, 2008,1, 133-140

Conference Papers

  • Junjie Yang, Yi Guo, Zuyun Yang, Chao Yang, A sparsity-relaxed algorithm for the under-determined convolutive blind source separation, 2nd International Conference on Image and Video Processing, and Artificial Intelligence, IVPAI 2019 [pdf]
  • Laurence Park, Yi Guo, Jesse Read, Assessing the multi-labelness of multi-label data, ECML, 2019 [pdf]
  • Kingshuk Mazumdar, Dongmo Zhang, Yi Guo, Multi-peak algorithmic trading strategies using Grey Wolf Optimizer, PRICAI, 2019
  • Kingshuk Mazumdar, Dongmo Zhang, Yi Guo, Portfolio Risk Optimisation and Diversification using Swarm Intelligence, PRICAI, 2019
  • Abdesselam Bouzerdoum, Philip B. Chapple, Mark Dras, Yi Guo, Len Hamey, Tahereh Hassanzadeh, Thanh Hoang Le, Omid Mohamad Nezami, Mehmet Orgun, Son Lam Phung, Christian Ritz, Maryam Shahpasand, Improved Deep-Learning-Based Classification of Mine-Like Contacts in Sonar Images from Autonomous Underwater Vehicles”, Proc. Underwater Acoustics Conference and Exhibition (UACE), 2019
  • Yi Guo, Simon Green, Laurence Park, Laren Rispen, Left Ventricle Volume Measuring Using Echocardiography Sequences, DICTA, 2018
  • Yang Liu, Yi Guo, Feng Li, Lei Xin, Puming Huang, A Fast Algorithm To Find All Paths For Hyperspectral Unmixing, IGARSS, 2018
  • Feng Li, Lei Xin, Yi Guo, Xiuping Jia, Multitemporal mid-infrared imagery based calibration and super resolution for Gaofen-4, IGARSS, 2018
  • Feng Li, Lei Xin, Yang Liu, Jie Fu, Yuhong Liu, Lanzhou, Yi Guo, High Efficient Optical Remote Sensing Images Acquisition For Nanosatellite Framework, SPIE, 2017
  • Junjie Yang, Zuyuan Yang, Yi Guo, Shengli Xie, Convolutive Blind Source Separation: Detecting Unknown Sources Number In Covariance Domain, The 9th International Conference on Computer and Automation Engineering (ICCAE 2017)
  • Jing Ke, Yi Guo, Arcot Sowmya, A Fast Approximate Spectral Unmixing Algorithm based on Segmentation, 13th IEEE CVPR workshop on Perception Beyond the Visible Spectrum 2017
  • Junbin Gao, Yi Guo, Zhiyong Wang, Matrix Neural Networks, International Symposium on Neural Networks (ISNN) 2017
  • Jing Ke, Yi Guo, Arcot Sowmya, Tomasz Bednarz, A Performance Acceleration Algorithm of Spectral Unmixing Via Subset Selection, European Symposium on Artificial Neural Networks (ESANN) 2017
  • Yi Guo, Feng Li, Peter Caccetta, Drew Devereux, Mark Berman, Cloud Filtering for Landsat TM Satellite Images Using Multiple Temporal Mosaicing. IGARSS 2016
  • Feng Li, Tim J. Cornwell, Frank de Hoog, Lei Xin, Yi Guo. Compressive sensing based multi-frequency synthesis, 2016 IEEE International Conference on Digital Signal Processing (DSP)
  • Ming Yin, Yi Guo, Junbin Gao, Zhaoshui He, Shengli Xie. Kernel Sparse Subspace Clustering on Symmetric Positive DefiniteManifolds, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016
  • Jing Ke, Arcot Sowmya, Yi Guo, Tomasz Bednarz, Michael Buckley. Efficient GPU Computing Framework of Cloud Filtering in Remotely Sensed Image Processing, International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2016
  • Yi Guo, Junbin Gao, Stephen Tierney, Feng Li, Ming Yin. Low Rank Sequential Subspace Clustering, IJCNN 2015
  • Stephen Tierney, Yi Guo, Junbin Gao. Selective Multi-Source Total Variation Image Restoration. DICTA2015
  • Zhipeng Hao, Mark Berman, Yi Guo, Glenn Stone, Iain Johnstone. Semi-Realistic Simulations of Natural Hyperspectral Scenes, IGARSS 2015
  • Feng Li, Yi Guo, Junbin Gao, Xiuping Jia. Hyperspectral Images Mapping with Group Sparse Representations, ICSPCC 2015
  • Stephen Tierney, Junbin Gao, Yi Guo. The W-Penalty and its Application to Alpha Matting with Sparse Labels. DICTA 2014
  • Stephen Tierney, Junbin Gao, Yi Guo. Affinity Pansharpening and Image Fusion. DICTA 2014
  • Ming Yin, Yi Guo, Junbin Gao. Linear Subspace Learning Approach via Sparse Dimension Reduction. IJCNN 2014
  • Junbin Gao, Xia hong, Yanfeng Sun, Yi Guo, Chris Harris. Dimensionality Reduction Assisted Tensor Clustering. IJCNN 2014
  • Stephen Tierney, Junbin Gao, Yi Guo. Subspace Clustering for Sequential Data. CVPR 2014
  • Xiao Tan, Changming Sun, Dadong Wang, Yi Guo, Tuan D. Pham. Soft Cost Aggregation with Multi-Resolution Fusion, ECCV 2014
  • Yi Guo, Junbin Gao, Fengyan Sun. Endmember Extraction by Exemplar Finder. ADMA 2013
  • Yi Guo, Junbin Gao, Feng Li. Large Scale Hyperspectral Data Segmentation by Random Spatial Subspace Clustering, IGARSS, 2013
  • Yi Guo, Junbin Gao, Feng Li. Dimensionality Reduction with Dimension Selection. PAKDD, 2013
  • Yi Guo, Junbin Gao, Feng Li. Spatial Subspace Clustering for Hyperspectral Data Segmentation, ICDIPC, 2013
  • Junbin Gao, Yi Guo, Ming Yin. Restricted Boltzmann Machine Approach to Couple Dictionary Training for Image Super-Resolution, ICIP2013
  • Xia Hong, Yi Guo, Sheng Chen, Junbin Gao, Sparse Model Construction using Coordinate Descent Optimization, DSP2013
  • Feng Li, Lingli Tang, Chuanrong Li, Yi Guo, Junbin Gao. A new super resolution method based on combinatorial sparse representation for remote sensing imagery. SPIE Remote Sensing, 2013
  • Feng Li, ChuanRong Li, LingLi Tang, Yi Guo. Elastic band-to-band registration for airborne multispectral scanners with large field of view. Europe Remote Sensing 2012
  • Yi Guo, Junbin Gao, Xia Hong. Constrained Group Sparsity, AI2012, 2012
  • Yi Guo, Junbin Gao. Local Feature Based Tensor Kernel for Image Manifold Learning, PAKDD2011, 2011
  • Yi Guo, Junbin Gao, Paul W. Kwan. Regularized Kernel Local Linear Embedding on Dimensionality Reduction for Non-vectorial Data, 2009, AI2009
  • Yi Guo, Junbin Gao, Paul W. Kwan. TKE with Relaxed Constraints on Dimensionality Reduction for Structured Data. Artificial Intelligence (AI) 2007
  • Paul W. Kwan, Yi Guo, Junbin Gao. A Learning Framework for Examiner-Centric Fingerprint Classification Using Spectral Features. International Symposium on Multispectral Image Processing & Pattern Recognition (MIPPR), 2007
  • Junbin Gao, Paul W. Kwan, Yi Guo. Robust L1 PCA and Its Application in Image Denoising, MIPPR, 2007
  • Yi Guo, Junbin Gao, Paul W. Kwan. Twin Kernel Embedding with Back Constraints. IEEE International Conference on Data Mining (ICDM) Workshops (High Performance Data Mining), 2007
  • Yi Guo, Junbin Gao, Paul W. Kwan. Learning Out-Of-Sample Mapping in Non-vectorial Data Reduction Using Constrained Twin Kernel Embedding. IEEE International Conference on Machine Learning and Cybernetics (ICMLC), 2007
  • Yi Guo, Junbin Gao, Paul W. Kwan. Learning Optimal Kernel from Distance Metric in Twin Kernel Embedding for Dimensionality Reduction and Visualization of Fingerprints. Proceeding of Advanced Data Mining Application (ADMA), 2007
  • Yi Guo, Junbin Gao. An Integration of Shape Context and Semigroup Kernel in Image Classification. IEEE ICMLC. 2007
  • Yi Guo, Junbin Gao, Paul W. Kwan, Kevin X. Hou. Visualization of Protein Structure Relationships Using Twin Kernel Embedding. IEEE International Conference on Bioinformatics and Biomedical Engineering (ICBBE). 2007
  • Yi Guo, Junbin Gao, Paul W. Kwan. Visualization of Non-vectorial Data Using Twin Kernel Embedding. Workshop on Artificial Intelligence and Data Mining (AIDM). 2006
  • Yi Guo, Junbin Gao, Paul W. Kwan. Kernel Laplacian Eigenmaps for Visualization of Non-vectorial Data. AI2006
  • Paul W. Kwan, Junbin Gao, Yi Guo. Fingerprint Matching Using Enhanced Shape Context. IVCNZ, 2006
  • Yi Guo, Junbin Gao. Manifolds of Bag of Pixels: A Better Representation for Image Recognition?, IEEE International Conference on SMC, 2006

Technical Reports

  • Yi Guo, Fast nonnegative least square algorithm. CMIS 2013
  • Yi Guo, Group Subset Selection with weights constraints. CMIS, 2012
  • Mark Berman, Leanne Bischof, Ryan Lagerstrom, Yi Guo, Jon Huntington and Peter Mason. An Unmixing Algorithm Based on a Large Library of Shortwave Infrared Spectra. CMIS, 2011
  • Yi Guo, Mark Berman. Version 7 of The Spectral Assistant: Software Description. CMIS, 2010
  • Yi Guo, Mark Berman. An Investigation of Some Regularization Approaches to the Unmixing of Mineral Reflectance Spectra. 2009
  • Yi Guo, Mark Berman. Version 6.2 of The Spectral Assistant (Shortwave Infrared Region) and Its Training Module: Developments and Software Description. 2008
  • Yi Guo, David Clifford, Mark Berman. Global Smoothing Module: Software Description. 2008
  • Yi Guo, Mark Berman. Version 6.3 of The Spectral Assistant (Shortwave Infrared Region) and a New Illite Test: Developments and Software Description. 2008
  • Yi Guo, Junbin Gao, Paul W. Kwan. Twin Measure Embedding. CSU, 2008
  • Yi Guo, Junbin Gao, Paul W. Kwan. Twin Kernel Embedding with Back Constraints. UNE, 2007

Code & demos

Research

My research interests are in machine learning, computational statistics and some applied mathematics such as optimisation, with applications in the areas such as computer vision, image analysis, remote sensing and in applied sciences as well such as environment monitoring, material science, medical science and so on.

 The models I worked on include

  • Dimensionality reduction
  • Manifold learning
  • Robust models
  • Blind source separation
  • Subspace clustering

 These methodologies have been applied to many problems in spectroscopy, remote sensing, computer vision, image processing, signal processing and so on.

 My recent research focuses on data science including 

  • spatial temporal models (for tensorial data) 
  • complex neural networks 
  • neural processing

If you are interested in pursue PhD study in machine learning or computational statistics, please contact me through emails.

Western Sydney University

Locked Bag 1797
Penrith NSW 2751

Tel: +61 2 9852 5222

ABN 53 014 069 881
CRICOS Provider No: 00917k