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

  • COMP3032 Machine Learning
  • INFO7001 Advanced Machine Learning
  • COMP3002/COMP7003 Applications of Big Data/Big Data
  • INFO7016,INFO7017 Master Project A&B
  • Optimisation, Under development

Publications & Code

Scholary books and chapters

Journal Articles

  1. Namal Jayasuriya, Yi Guo, Wen Hu and Oula Ghannoum, Machine Vision based Plant Height Estimation for Protected Crop Facilities. Computers and Electronics in Agriculture, 2024. [pdf]
  2. Yi Guo, Feng Li and Zhuo Wang, Cloud Removal Using Scattering Model and Evaluation via Semi-realistic simulation. International Journal of Remote Sensing, 2023. [pdf][code]
  3. Zhiqi Shao, Dai Shi, Andi Han, Andrey Vasnev, Yi Guo and Junbin Gao, Enhancing framelet GCNs with generalized p-Laplacian regularization. International Journal of Machine Learning and Cybernetics, 2023 [pdf][code]
  4. Ke, Jing, Yiqing Shen, Yizhou Lu, Yi Guo, and Dinggang Shen, Mine Local Homogeneous Representation by Interaction Information Clustering with Unsupervised Learning in Histopathology Images, Computer Methods and Programs in Biomedicine 235, 2023
  5. Ke Jing, Yizhou Lu, Yiqing Shen, Junchao Zhu, Yijin Zhou, Jinghan Huang, Jieteng Yao, Xiaoyao Liang, Yi Guo, Zhonghua Wei, Sheng Liu, Qin Huang, Fusong Jiang, Dinggang Shen, ClusterSeg: A Crowd Cluster Pinpointed Nucleus Segmentation Framework with Cross-Modality Datasets. Medical Image Analysis 85, 2023
  6. Xue Yang, Liang Liang, Feng Li, Qingjiu Tian, Xiaotian Lu, Lei Xin, Yi Guo, Wenjun Dong, Hyper-Temporal Data Based Modulation Transfer Functions Compensation for Geostationary Remote Sensing Satellites. IEEE Transactions on Geoscience and Remote Sensing, 2022
  7. Elise Baker, Weicong Li, Rosemary Hodges, Sarah Masso, Caroline Jones, Yi Guo, Mary Alt, et al. 2022. Harnessing Automatic Speech Recognition to Realise Sustainable Development Goals 3, 9, and 17 through Interdisciplinary Partnerships for Children with Communication Disability, International Journal of Speech-Language Pathology, 2022
  8. Yi Guo, Stephen Tierney, Junbin Gao, Efficient Sparse Subspace Clustering by Nearest Neighbour Filtering, Signal Processing, 2021 [pdf][Matlab code]
  9. Yi Guo, Stephen Tierney, Junbin Gao, Robust Functional Manifold Clustering, IEEE Transactions on Neural Networks and Learning Systems, 2020 [pdf][Matlab code]
  10. Kingshuk Mazumdar, Dongmo Zhang, Yi Guo, Portfolio selection and unsystematic risk optimisation using swarm intelligence, Journal of Banking and Financial Technology, 2019
  11. 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][Matlab code]
  12. 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][Matlab code]
  13. 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]
  14. 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]
  15. 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]
  16. Yi Guo, Feng Li, Peter Caccetta, Drew Devereux, Multiple Temporal Mosaicing for Landsat TM Satellite Images, Journal of Applied Remote Sensing, 2017
  17. 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
  18. 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
  19. Xia Hong, Sheng Chen, Yi Guo, Junbin Gao, L1 Norm Penalized Orthogonal Forward Regression, International Journal of Systems Sciences, 2017
  20. 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
  21. 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
  22. 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
  23. 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
  24. 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 Information, BMC Genomics, 2016
  25. David Clifford, Yi Guo. Combining two soil property rasters using an adaptive gating approach. Soil Research, 2015
  26. 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
  27. Ming Yin, Junbin Gao, Yi Guo. A Nonlinear Low-rank Representation on Stiefel Manifold, Electronics Letters, 2015
  28. Yi Guo, Junbin Gao, Feng Li. Random Spatial Subspace Clustering. Knowledge-Based Systems, 2014
  29. Yi Guo, Mark Berman and Junbin Gao. Group Subset Selection for Linear Regression. Computational Statistics and Data Analysis, 2014
  30. Yi Guo, Junbin Gao, Feng Li. Spatial Subspace Clustering for Drill Hole Spectral Data, Journal of Applied Remote Sensing, 2014
  31. 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
  32. Feng Li, ChuanRong Li, LingLi Tang, Yi Guo. Elastic registration for airborne multispectral line scanners, Journal of Applied Remote Sensing, 2014
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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

  1. Xun Yao, Ruyi He, Xinrong Hu, Jie Yang, Yi Guo, and Zijian Huang Improving Adversarially Robust Sequential Recommendation through Generalizable Perturbations. Big Data, 2023
  2. Dai Shi, Andi Han, Junbin Gao and Yi Guo A New Perspective On the Expressive Equivalence Between Graph Convolution and Attention Models. ACML, 2023
  3. Jie Yang and Yi Guo SCAD: Subspace Clustering based Adversarial Detector. WSDM, 2023 [pdf]
  4. Jie Yang and Yi Guo COTER: Conditional Optimal Transport meets Table Retrieval. WSDM, 2023 [pdf]
  5. Xun Yao, Junlong Ma, Xinrong Hu, Jie Yang and Yi Guo. Towards robust token embeddings for Extractive Question Answering. International Conference on Web Information Systems Engineering (WISE), 2023 [pdf]
  6. Xun Yao, Qihang Yang, Xinrong Hu, Jie Yang and Yi Guo. CREAM: Named Entity Recognition with Concise query and Region-Aware Minimization. International Conference on Web Information Systems Engineering (WISE), 2023
  7. Junping Liu, Mingkang Gong, Xinrong Hu, Jie Yang, and Yi Guo MIRS: [MASK] Insertion based Retrieval Stabilizer for Query Variations. International Conference on Database and Expert Systems Applications (DEXA), 2023 [pdf]
  8. Dai Shi, Andi Han, Junbin Gao, and Yi Guo. Fixed Point Laplacian Mapping: A Geometrically Correct Manifold Learning Algorithm. IJCNN, 2023 [pdf][code]
  9. Xinrong Hu, Ce Xu, Junlong Ma, Zijian Huang, Jie Yang, Yi Guo and Johan Barthelemy[MASK] Insertion: a robust method for anti-adversarial attacks. EACL, 2023 [pdf]
  10. Junping Liu, Shijie Mei, Xinrong Hu, Xun Yao, Jack Yang, and Yi Guo. Seeing the wood for the trees: a contrastive regularization method for the low-resource Knowledge Base Question Answering. NAACL, 2022 [pdf][code]
  11. Junwei Deng, Yiqing Shen, Yi Guo, Jing Ke, CellSegNet: An Adaptive Multi-resolution Hybrid Network for Cell Segmentation. SPIE Medical Imaging, 2022
  12. Liu Yang, Junjie Yang and Yi Guo, Under-determined Blind Speech Separation via the Convolutive Transfer Function and lp Regularization. ICMSN, 2021
  13. Jing Ke, Yiqing Shen, Xinyu Jiang, Yi Guo, Yaobing Chen, Xiaoyao Liang, Multiple-datasets and multiple-label based color normalization in histopathology with cGAN, Medical Imaging 2021: Digital Pathology
  14. Jing Ke, Yiqing Shen, Yi Guo, Xiaoyao Liang, Fast Tumor Detector in Whole-Slide Image With Dynamic Programing Based Monte Carlo Sampling, IEEE ICIP 2020
  15. Jing Ke, Yiqing Shen, Yi Guo, Jason D. Wright, Naifeng Jing and Xiaoyao Liang, A high-throughput tumor location system with deep learning for colorectal cancer histopathology image, Proceedings of the 18th International Conference on Artificial Intelligence in Medicine, AIME 2020
  16. Jing Ke, Yiqing Shen, Yi Guo, Jason D. Wright, and Xiaoyao Liang, A prediction model of microsatellite status from histology images, in Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology, 2020
  17. 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]
  18. Laurence Park, Yi Guo, Jesse Read, Assessing the multi-labelness of multi-label data, ECML, 2019 [pdf]
  19. Kingshuk Mazumdar, Dongmo Zhang, Yi Guo, Multi-peak algorithmic trading strategies using Grey Wolf Optimizer, PRICAI, 2019
  20. Kingshuk Mazumdar, Dongmo Zhang, Yi Guo, Portfolio Risk Optimisation and Diversification using Swarm Intelligence, PRICAI, 2019
  21. 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
  22. Yi Guo, Simon Green, Laurence Park, Laren Rispen, Left Ventricle Volume Measuring Using Echocardiography Sequences, DICTA, 2018
  23. Yang Liu, Yi Guo, Feng Li, Lei Xin, Puming Huang, A Fast Algorithm To Find All Paths For Hyperspectral Unmixing, IGARSS, 2018
  24. Feng Li, Lei Xin, Yi Guo, Xiuping Jia, Multitemporal mid-infrared imagery based calibration and super resolution for Gaofen-4, IGARSS, 2018
  25. 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
  26. Junjie Yang, Zuyuan Yang, Yi Guo, Shengli Xie, Blind Source Separation: Detecting Unknown Sources Number In Covariance Domain, The 9th International Conference on Computer and Automation Engineering (ICCAE 2017)
  27. 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
  28. Junbin Gao, Yi Guo, Zhiyong Wang, Matrix Neural Networks, International Symposium on Neural Networks (ISNN) 2017 [python code]
  29. 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
  30. Yi Guo, Feng Li, Peter Caccetta, Drew Devereux, Mark Berman, Cloud Filtering for Landsat TM Satellite Images Using Multiple Temporal Mosaicing. IGARSS 2016
  31. 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)
  32. 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
  33. 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
  34. Yi Guo, Junbin Gao, Stephen Tierney, Feng Li, Ming Yin. Low Rank Sequential Subspace Clustering, IJCNN 2015
  35. Stephen Tierney, Yi Guo, Junbin Gao. Selective Multi-Source Total Variation Image Restoration. DICTA2015
  36. Zhipeng Hao, Mark Berman, Yi Guo, Glenn Stone, Iain Johnstone. Semi-Realistic Simulations of Natural Hyperspectral Scenes, IGARSS 2015
  37. Feng Li, Yi Guo, Junbin Gao, Xiuping Jia. Hyperspectral Images Mapping with Group Sparse Representations, ICSPCC 2015
  38. Stephen Tierney, Junbin Gao, Yi Guo. The W-Penalty and its Application to Alpha Matting with Sparse Labels. DICTA 2014
  39. Stephen Tierney, Junbin Gao, Yi Guo. Affinity Pansharpening and Image Fusion. DICTA 2014
  40. Ming Yin, Yi Guo, Junbin Gao. Linear Subspace Learning Approach via Sparse Dimension Reduction. IJCNN 2014
  41. Junbin Gao, Xia hong, Yanfeng Sun, Yi Guo, Chris Harris. Dimensionality Reduction Assisted Tensor Clustering. IJCNN 2014
  42. Stephen Tierney, Junbin Gao, Yi Guo. Subspace Clustering for Sequential Data. CVPR 2014
  43. Xiao Tan, Changming Sun, Dadong Wang, Yi Guo, Tuan D. Pham. Soft Cost Aggregation with Multi-Resolution Fusion, ECCV 2014
  44. Yi Guo, Junbin Gao, Fengyan Sun. Endmember Extraction by Exemplar Finder. ADMA 2013
  45. Yi Guo, Junbin Gao, Feng Li. Large Scale Hyperspectral Data Segmentation by Random Spatial Subspace Clustering, IGARSS, 2013
  46. Yi Guo, Junbin Gao, Feng Li. Dimensionality Reduction with Dimension Selection. PAKDD, 2013
  47. Yi Guo, Junbin Gao, Feng Li. Spatial Subspace Clustering for Hyperspectral Data Segmentation, ICDIPC, 2013
  48. Junbin Gao, Yi Guo, Ming Yin. Restricted Boltzmann Machine Approach to Couple Dictionary Training for Image Super-Resolution, ICIP2013
  49. Xia Hong, Yi Guo, Sheng Chen, Junbin Gao, Sparse Model Construction using Coordinate Descent Optimization, DSP2013
  50. 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
  51. 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
  52. Yi Guo, Junbin Gao, Xia Hong. Constrained Group Sparsity, AI2012, 2012
  53. Yi Guo, Junbin Gao. Local Feature Based Tensor Kernel for Image Manifold Learning, PAKDD2011, 2011
  54. Yi Guo, Junbin Gao, Paul W. Kwan. Regularized Kernel Local Linear Embedding on Dimensionality Reduction for Non-vectorial Data, 2009, AI2009
  55. Yi Guo, Junbin Gao, Paul W. Kwan. Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data. Artificial Intelligence (AI) 2007
  56. 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
  57. Junbin Gao, Paul W. Kwan, Yi Guo. Robust L1 PCA and Its Application in Image Denoising, MIPPR, 2007
  58. 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
  59. 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
  60. 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
  61. Yi Guo, Junbin Gao. An Integration of Shape Context and Semigroup Kernel in Image Classification. IEEE ICMLC. 2007
  62. 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
  63. 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
  64. Yi Guo, Junbin Gao, Paul W. Kwan. Kernel Laplacian Eigenmaps for Visualization of Non-vectorial Data. AI2006
  65. Paul W. Kwan, Junbin Gao, Yi Guo. Fingerprint Matching Using Enhanced Shape Context. IVCNZ, 2006
  66. Yi Guo, Junbin Gao. Manifolds of Bag of Pixels: A Better Representation for Image Recognition?, IEEE International Conference on SMC, 2006

Preprints

  1. Andrew Francis, Yi Guo, Paul Herley, Oliver Obst, Laurence Park, Mark Tanaka, Russell Thomson and X. Rosalind Wang, Projected ICU and Mortuary load due to COVID-19 in Sydney[pdf]

Technical Reports

  1. Yi Guo, Fast nonnegative least square algorithm. CMIS 2013
  2. Yi Guo, Group Subset Selection with weights constraints. CMIS, 2012
  3. 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
  4. Yi Guo, Mark Berman. Version 7 of The Spectral Assistant: Software Description. CMIS, 2010
  5. Yi Guo, Mark Berman. An Investigation of Some Regularization Approaches to the Unmixing of Mineral Reflectance Spectra. 2009
  6. Yi Guo, Mark Berman. Version 6.2 of The Spectral Assistant (Shortwave Infrared Region) and Its Training Module: Developments and Software Description. 2008
  7. Yi Guo, David Clifford, Mark Berman. Global Smoothing Module: Software Description. 2008
  8. Yi Guo, Mark Berman. Version 6.3 of The Spectral Assistant (Shortwave Infrared Region) and a New Illite Test: Developments and Software Description. 2008
  9. Yi Guo, Junbin Gao, Paul W. Kwan. Twin Measure Embedding. CSU, 2008
  10. 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 

  • Natural Language Processing (NLP) modeling
  • 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