Academic Experience

Publications and Conference Proceedings

Publications

The subglacial landscape and hydrology of Antarctica mapped from space

• Thesis at Victoria University of Wellington - Te Herenga Waka, 2021

• Citation: Leong, W. J. (2021). The subglacial landscape and hydrology of Antarctica mapped from space [PhD thesis, Victoria University of Wellington | Te Herenga Waka]. https://doi.org/10.26686/wgtn.14956062.v1

• Links: Doi, Talk, Github

  

DeepBedMap: A deep neural network for resolving the bed topography of Antarctica

• Paper at The Cryosphere, 2020

• Citation: Leong, W. J., & Horgan, H. J. (2020). DeepBedMap: A deep neural network for resolving the bed topography of Antarctica. The Cryosphere, 14(11), 3687–3705. https://doi.org/10.5194/tc-14-3687-2020

• Links: Doi, Github

  

Presentations

DeepSlide: Self-supervised learning on SAR data for change detection

• Presentation at AGU Fall Meeting, 2022

• Citation: Leong, W. J., Mahesh, R. B., Prapas, I., Boehm, V., Ramos-Pollan, R., Nemni, E., Kalaitzis, F., & Ganju, S. (2022, December 16). DeepSlide: Self-supervised learning on SAR data for change detection. AGU 2022 Fall Meeting, Chicago, IL & Online Everywhere.

• Links: Abstract, Doi, Slides, Gitlab

  

DeepBedMap: A Super-Resolution Generative Adversarial Network for resolving the subglacial topography of Antarctica

• Presentation at Machine Learning for Polar Regions Workshop, 2022

• Citation: Leong, W. J., & Horgan, H. J. (2022, June 17). DeepBedMap: A Super-Resolution Generative Adversarial Network for resolving the subglacial topography of Antarctica. Machine Learning for Polar Regions Workshop, Lamont-Doherty Earth Observatory, virtual. https://www.climate.columbia.edu/events/machine-learning-polar-regions-workshop

• Links: Abstract, Youtube, Slides, Github

  

Teaching machines about our planet: Viewing, Learning, Imagining

• Presentation at OSU EARTHSC 8898 Seminar, 2022

• Citation: Leong, W. J. (2022, April 08). Teaching machines about our planet: Viewing, Learning, Imagining. OSU EARTHSC 8898 Seminar, virtual. https://earthsciences.osu.edu/events/wei-ji-leong-earthsc-8898-teaching-machines-about-our-planet-viewing-learning-imagining

• Links: Abstract, Slides, Github

  

DeepBedMap: A Super-Resolution Generative Adversarial Network for resolving the bed topography of Antarctica

• Presentation at CEDSG Seminar Series, 2020

• Citation: Leong, W. J., & Horgan, H. J. (2020, October 20). DeepBedMap: A Super-Resolution Generative Adversarial Network for resolving the bed topography of Antarctica. CEDSG Seminar Series, virtual. https://talks.cam.ac.uk/talk/index/152497

• Links: Abstract, Slides

DeepBedMap: A super-resolution deep neural network for resolving the bed topography of Antarctica

• Presentation at IGS Five Decades of Radioglaciology Symposium, 2019

• Citation: Leong, W. J., & Horgan, H. J. (2019, July 10). DeepBedMap: A super-resolution deep neural network for resolving the bed topography of Antarctica. IGS Five Decades of Radioglaciology Symposium, Stanford, California, United States. https://www.igsoc.org/symposia/2019/stanford/proceedings/procsfiles/procabstracts_75.html#A3032

• Links: Abstract, Slides

Posters

H2OvalNet: Detecting Fairy Circles from Sentinel-2 imagery in Australia

• Poster at AGU Fall Meeting, 2022

• Citation: Leong, W. J., Yadav, B., Negrete, A., Howat, I., & Moortgat, J. (2022, December 13). H2OvalNet: Detecting Fairy Circles from Sentinel-2 imagery in Australia. AGU 2022 Fall Meeting, Chicago, IL & Online Everywhere. https://doi.org/10.22541/essoar.167214400.07921060/v1

• Links: Abstract, Poster, Github

  

Collaborative Computational Resource Development around ICESat-2 Data: the icepyx Community and Library

• Poster at AGU Fall Meeting, 2021

• Citation: Scheick, J., Bisson, K., Li, T., Leong, W. J., & Arendt, A. A. (2021, December 17). Collaborative Computational Resource Development around ICESat-2 Data: the icepyx Community and Library. AGU 2021 Fall Meeting, virtual. https://doi.org/10.1002/essoar.10511316.1

• Links: Abstract, Poster, Github

  

PyGMT: An open-source Python library for geospatial processing, analysis, and visualization

• E-lightning at AGU Fall Meeting, 2021

• Citation: Jones, M., Grund, M., Schlitzer, W., Leong, W. J., Tian, D., Yao, J. & Uieda, L. (2021, December 17). PyGMT: An open-source Python library for geospatial processing, analysis, and visualization. AGU 2021 Fall Meeting, virtual.

• Links: Abstract, Poster, Youtube, Github

  

Spatiotemporal variability of active subglacial lakes in Antarctica from 2018-2021 using ICESat-2 laser altimetry

• Poster at AGU Fall Meeting, 2021

• Citation: Leong, W. J., & Horgan, H. J. (2021, December 14). Spatiotemporal variability of active subglacial lakes in Antarctica from 2018-2021 using ICESat-2 laser altimetry. AGU 2021 Fall Meeting, virtual. https://doi.org/10.1002/essoar.10510996.1

• Links: Abstract, Poster, Github

  

Spatiotemporal variability of active subglacial lakes in Antarctica from 2018-2020 using ICESat-2 laser altimetry

• Poster at New Zealand Antarctic Science Conference, 2021

• Citation: Leong, W. J., & Horgan, H. J. (2021, February 10). Spatiotemporal variability of active subglacial lakes in Antarctica from 2018-2020 using ICESat-2 laser altimetry. New Zealand Antarctic Science Conference, Christchurch, New Zealand. https://doi.org/10.13140/RG.2.2.27952.07680

• Links: Abstract, Poster, Github

  

DeepBedMap: Resolving the bed topography of Antarctica with a deep neural network

• Poster at SCAR 2020, 2020

• Citation: Leong, W. J., & Horgan, H. J. (2020, October 6). DeepBedMap: Resolving the bed topography of Antarctica with a deep neural network. SCAR 2020, virtual. https://doi.org/10.1002/essoar.10506291.1

• Links: Abstract, Poster, Github

  

DeepBedMap: Using a deep neural network to better resolve the bed topography of Antarctica

• Poster at EGU General Assembly, 2019

• Citation: Leong, W. J., & Horgan, H. J. (2019, April 9). DeepBedMap: Using a deep neural network to better resolve the bed topography of Antarctica. EGU General Assembly, Vienna, Austria. https://presentations.copernicus.org/EGU2019/EGU2019-11945_presentation.pdf

• Links: Abstract, Poster, Github