UC Research Profile - University of Canterbury

Mr Heyang (Thomas) Li

Contact

Department: Mathematics and Statistics

Email: thomas.li@canterbury.ac.nz

Direct Dial: +64 3 3693052

Office: Jack Erskine 720

Language: English

About

Research / Creative works

Networks

Fields of Research

Classification Trees
Deep Learning
Image Classification and Regression
X-ray CT Image Processing
Phylogenetic Trees
Multi-Grid Learning Methods
High Performance and GPU Computing Application

Researcher Summary

Thomas is a Lecturer in Statistics and Data Science at University of Canterbury (UC), School of Mathematics and Statistics. His current research areas involve image processing and classification, 3D projective geometry, phylogenetic trees, classification trees, and deep learning applications. He currently leads the UC Spatial And Image Learning (SAIL) group, working on research in collaboration with NZ Transport Agency, Christchurch City Council, Christchurch Airport and Stats NZ. UC SAIL group is kindly support by the School, UC R&I and KiwiNet.

Thomas completed his PhD research at The Australian National University, in the Department of Applied Mathematics, he worked on image processing algorithms for Computed Tomography. The outcome of his PhD research improved the signal to noise properties. He has published papers in highly ranked international peer reviewed journals, presentations at international conferences, obtained over $400k of research grants, and two US patent publications for which he was one of the inventors.

Thomas has a wide research network in Australia and New Zealand, and are open to related research collaborations, and interests from prospective PhD students.

Subject Area: Disciplines

Computer Science, Information Technology, Information Sciences: Algorithm Engineering ; Computer Vision
Mathematics: Applied Mathematics ; Biomathematics
Statistics: Applied Statistics ; Statistics

Prizes and Awards

BHP Phase-X optimisation challenge ( 2016 - present )

Invited presentation at Australian Society for Operations Research conference ( 2016 - present )

Research/Scholarly/Creative Works

Li H., Todd Z. and Bielski N. (2023) Equirectangular Image Data Detection, Segmentation and Classification of Varying Sized Traffic Signs: A Comparison of Deep Learning Methods. Sensors 23(7) http://dx.doi.org/10.3390/s23073381. (Journal Articles)

Alloo SJ., Paganin DM., Morgan KS., Kitchen MJ., Stevenson AW., Mayo SC., Li HT., Kennedy BM., Maksimenko A. and Bowden JC. (2022) Dark-field tomography of an attenuating object using intrinsic x-ray speckle tracking. Journal of Medical Imaging 9(3) http://dx.doi.org/10.1117/1.JMI.9.3.031502. (Journal Articles)

Li HT., Todd Z., Bielski N. and Carroll F. (2022) 3D lidar point-cloud projection operator and transfer machine learning for effective road surface features detection and segmentation. Visual Computer 38(5): 1759-1774. http://dx.doi.org/10.1007/s00371-021-02103-8. (Journal Articles)

Maliszewski KA., Vetrova V., Li H., Kolenderski P. and Kolenderska SM. (2022) Dispersion-contrast imaging using machine learning. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE 11948 http://dx.doi.org/10.1117/12.2612671. (Conference Contributions - Published)

Alloo SJ., Paganin DM., Morgan KS., Kitchen MJ., Stevenson AW., Mayo SC., Li HT., Kennedy BM., Maksimenko A. and Bowden J. (2021) Speckle-Based X-Ray Dark-Field Tomography of an Attenuating Object. In Proceedings of SPIE - The International Society for Optical Engineering 11840 http://dx.doi.org/10.1117/12.2597722. (Conference Contributions - Published)

Pavlov KM., Paganin DM., Morgan KS., Li H., Berujon S., Quénot L. and Brun E. (2021) Directional dark-field implicit x-ray speckle tracking using an anisotropic-diffusion Fokker-Planck equation. Physical Review A 104(5) http://dx.doi.org/10.1103/PhysRevA.104.053505. (Journal Articles)

Li HT., Schaff F., Croton LCP., Morgan KS. and Kitchen MJ. (2020) Quantitative material decomposition using linear iterative near-field phase retrieval dual-energy X-ray imaging. Physics in Medicine and Biology 65(18) http://dx.doi.org/10.1088/1361-6560/ab9558. (Journal Articles)

Pavlov KM., Li HT., Paganin DM., Berujon S., Rougé-Labriet H. and Brun E. (2020) Single-shot x-ray speckle-based imaging of a single-material object. Physical Review Applied 13(5) 054023 http://dx.doi.org/10.1103/PhysRevApplied.13.054023. (Journal Articles)

Pavlov KM., Paganin DM., Li HT., Berujon S., Rougé-Labriet HN. and Brun E. (2020) X-ray multi-modal intrinsic-speckle-tracking. Journal of Optics (United Kingdom) 22(12) http://dx.doi.org/10.1088/2040-8986/abc313. (Journal Articles)

Herbst L., Li H. and Steel M. (2019) Quantifying the accuracy of ancestral state prediction in a phylogenetic tree under maximum parsimony. Journal of Mathematical Biology 78(6): 1953-1979. http://dx.doi.org/10.1007/s00285-019-01330-x. (Journal Articles)

Kingston A., Latham S., Sheppard A., Myers G., Recur B., Li HT. and Varslot T. (2019) Acquisition and processing of data in a tomographic imaging apparatus.Patent No. US 10254419 B2. (Intellectual Property)

Li HT., Schaff F., Croton L., Morgan K. and Kitchen M. (2019) Material Splitting by Near-Field Dual-Energy X-ray Phase Retrieval. In https://currinda.s3.amazonaws.com/ann/Abstrakt-FullPaper/86/5c6a3a70e8077-ICTMS_Abstract_2019_Thomas_PhaseRetrieval_FSMK.pdf. (Conference Contributions - Published)

MAYO S., BOWDEN J., Li HT., PAGANIN D., Pavlov K., MAKSIMENKO A., Kennedy B., KITCHEN M. and STEVENSON A. (2019) Preliminary results from speckle-tracking studies at IMBL. In. (Conference Contributions - Published)

Pavlov KM., Li HT., Paganin DM., Berujon S., Labriet H. and Brun E. (2019) X-ray speckle-based imaging of a single-material object. Beyond the geometric-flow formalism.. In. (Conference Contributions - Published)

Kingston A., Latham S., Sheppard A., Myers G., Recur B. and Li HT. (2018) Data processing in a tomographic imaging apparatus.Patent No. US 10078057 B2. (Intellectual Property)

Kingston A., Myers G., Latham S., Recur B., Li H. and Sheppard A. (2018) Space-filling X-ray source trajectories for efficient scanning in large-angle cone-beam computed tomography. IEEE Transactions on Computational Imaging 4(3): 447-458. http://dx.doi.org/10.1109/TCI.2018.2841202. (Journal Articles)

Kingston A., Latham S., Sheppard A., Myers G., Recur B. and Li H. (2017) Novel data processing in a tomographic imaging apparatus.Patent No. US20170059493A1, US. (Intellectual Property)

Kingston A., Latham S., Sheppard A., Myers G., Recur B., Li H. and Varslot T. (2017) Novel acquisition and processing of data in a tomographic image apparatus.Patent No. US 20170052264. (Intellectual Property)

Li H. (2017) Partially Coherent Lab Based X-ray Micro Computed Tomography. Canberra. The Australian National University. (Theses / Dissertations)

Li H. and Candy R. (2017) Optimising Open-Pit Mining Using Multi-Grid Search. In https://www.mssanz.org.au/modsim2017/documents/MODSIM2017_book_abstracts.pdf. (Conference Contributions - Published)

Li H., Katz-Boon H., Myers G., Kingston A., Svalbe I. and Etheridge J. (2017) Atomic Resolution Binary Tomography of Gold Nanorod Surface Morphology. In Proceedings of ICTMS2017https://meetingorganizer.copernicus.org/ICTMS2017/ICTMS2017-201.pdf. (Conference Contributions - Published)

Li HT., Kingston AM., Myers GR., Beeching L. and Sheppard AP. (2017) Linear iterative near-field phase retrieval (LIPR) for dual-energy x-ray imaging and material discrimination. Journal of the Optical Society of America A 35(1) A30 http://dx.doi.org/10.1364/JOSAA.35.000A30. (Journal Articles)

M B., Li H., Stephenson A., Toscas P. and Zhu Z. (2017) Quantitative Cyber Risk Model and Optimal Mitigation. In Proceedings of MODSIM2017: 1843-1849. (Conference Contributions - Published)

Kingston A., Myers G., Latham S., Li H., Veldkamp J. and Sheppard A. (2016) Optimized x-ray source scanning trajectories for iterative reconstruction in high cone-angle tomography. In Proceedings of SPIE: Developments in X-Ray Tomography X 9967: 11. http://dx.doi.org/10.1117/12.2238297. (Conference Contributions - Published)

Myers G., Kingston A., Latham S., Recur B., Li H., Turner M., Beeching L. and Sheppard A. (2016) Rapidly converging multigrid reconstruction of cone-beam tomographic data. In Proceedings of SPIE: Developments in X-Ray Tomography X 9967: 7. http://dx.doi.org/10.1117/12.2238267. (Conference Contributions - Published)

Li H., Kingston A., Myers G., Recur B. and Sheppard A. (2015) 3D X-Ray Source Deblurring in High Cone-Angle Micro-CT. IEEE Transactions on Nuclear Science 62(5): 2075-2084. http://dx.doi.org/10.1109/TNS.2015.2435782. (Journal Articles)

Kingston A., Li H., Normand N. and Svalbe I. (2014) Fourier Inversion of the Mojette transform. In Lecture Notes in Computer Science (LNCS): Discrete Geometry for Computer Imagery 8668: 275-284. Springer Verlag. http://dx.doi.org/10.1007/978-3-319-09955-2_23. (Conference Contributions - Published)

Li H., Kingston A., Myers G., Recur B., Turner M. and Sheppard A. (2014) Improving spatial-resolution in high cone-angle micro-CT by source deblurring. In Proceedings of SPIE - The International Society for Optical Engineering 9212 http://dx.doi.org/10.1117/12.2062415. (Conference Contributions - Published)

Mooers A., Gascuel O., Stadler T., Li H. and Steel M. (2012) Branch lengths on Yule trees and the expected loss of phylogenetic diversity. Systematic Biology 61(2): 195-203. http://dx.doi.org/10.1093/sysbio/syr090. (Journal Articles)

Review and Refereeing

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The 22nd International Congress on Modelling and Simulation ( 2017 - 2023)

Research Groups

Spatial And Image Learning (SAIL) Team