Ching‐Yao Lai

999 total citations
27 papers, 605 citations indexed

About

Ching‐Yao Lai is a scholar working on Atmospheric Science, Pulmonary and Respiratory Medicine and Management, Monitoring, Policy and Law. According to data from OpenAlex, Ching‐Yao Lai has authored 27 papers receiving a total of 605 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Atmospheric Science, 6 papers in Pulmonary and Respiratory Medicine and 6 papers in Management, Monitoring, Policy and Law. Recurrent topics in Ching‐Yao Lai's work include Cryospheric studies and observations (13 papers), Landslides and related hazards (6 papers) and Winter Sports Injuries and Performance (6 papers). Ching‐Yao Lai is often cited by papers focused on Cryospheric studies and observations (13 papers), Landslides and related hazards (6 papers) and Winter Sports Injuries and Performance (6 papers). Ching‐Yao Lai collaborates with scholars based in United States, United Kingdom and Switzerland. Ching‐Yao Lai's co-authors include Howard A. Stone, Jens Eggers, Luc Deike, Emilie Dressaire, Martin Wearing, Pierre Gentine, Jan Melchior van Wessem, Po-Hsuan Cameron Chen, Jonathan Kingslake and Julian J. Spergel and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Ching‐Yao Lai

24 papers receiving 596 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ching‐Yao Lai United States 12 212 168 154 108 106 27 605
Samuel S. Pegler United Kingdom 12 203 1.0× 57 0.3× 64 0.4× 39 0.4× 105 1.0× 28 381
Duncan R. Hewitt United Kingdom 18 81 0.4× 173 1.0× 394 2.6× 128 1.2× 39 0.4× 50 868
М.Э. Эглит Russia 11 128 0.6× 50 0.3× 114 0.7× 44 0.4× 13 0.1× 39 373
Steven Roper United Kingdom 13 89 0.4× 38 0.2× 57 0.4× 84 0.8× 46 0.4× 22 634
Mario Martinelli Netherlands 18 168 0.8× 28 0.2× 244 1.6× 80 0.7× 68 0.6× 73 1.0k
Xiao Jing Zheng China 16 112 0.5× 73 0.4× 65 0.4× 149 1.4× 27 0.3× 28 816
François Rioual France 12 69 0.3× 46 0.3× 230 1.5× 53 0.5× 154 1.5× 19 552
Kjetil Thøgersen Norway 10 88 0.4× 49 0.3× 29 0.2× 65 0.6× 37 0.3× 18 363
Laurent Lacaze France 18 82 0.4× 133 0.8× 589 3.8× 26 0.2× 6 0.1× 45 900
I. Ippolito Argentina 17 42 0.2× 186 1.1× 456 3.0× 210 1.9× 5 0.0× 71 786

Countries citing papers authored by Ching‐Yao Lai

Since Specialization
Citations

This map shows the geographic impact of Ching‐Yao Lai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ching‐Yao Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ching‐Yao Lai more than expected).

Fields of papers citing papers by Ching‐Yao Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching‐Yao Lai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ching‐Yao Lai. The network helps show where Ching‐Yao Lai may publish in the future.

Co-authorship network of co-authors of Ching‐Yao Lai

This figure shows the co-authorship network connecting the top 25 collaborators of Ching‐Yao Lai. A scholar is included among the top collaborators of Ching‐Yao Lai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ching‐Yao Lai. Ching‐Yao Lai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lai, Ching‐Yao, et al.. (2025). Seasonal changes of mélange thickness coincide with Greenland calving dynamics. Nature Communications. 16(1). 573–573. 4 indexed citations
2.
Wang, Y., et al.. (2025). Deep learning the flow law of Antarctic ice shelves. Science. 387(6739). 1219–1224. 5 indexed citations
3.
Wang, Y. & Ching‐Yao Lai. (2024). Multi-stage neural networks: Function approximator of machine precision. Journal of Computational Physics. 504. 112865–112865. 20 indexed citations
4.
Vecchi, Gabriel A., et al.. (2024). Realistic tropical cyclone wind and pressure fields can be reconstructed from sparse data using deep learning. Communications Earth & Environment. 5(1). 14 indexed citations
5.
Lai, Ching‐Yao, Pedram Hassanzadeh, Aditi Sheshadri, et al.. (2024). Machine Learning for Climate Physics and Simulations. Annual Review of Condensed Matter Physics. 16(1). 343–365. 9 indexed citations
6.
Stevens, Laura A., Sarah B. Das, M. D. Behn, et al.. (2024). Elastic Stress Coupling Between Supraglacial Lakes. Journal of Geophysical Research Earth Surface. 129(5). 2 indexed citations
7.
Lai, Ching‐Yao, et al.. (2024). Theoretical stability of ice shelf basal crevasses with a vertical temperature profile. Journal of Glaciology. 70. 3 indexed citations
8.
Culberg, Riley, et al.. (2024). Vulnerability of firn to hydrofracture: poromechanics modeling. Journal of Glaciology. 70. 1 indexed citations
9.
Lai, Ching‐Yao, et al.. (2023). One-dimensional ice shelf hardness inversion: Clustering behavior and collocation resampling in physics-informed neural networks. Journal of Computational Physics. 492. 112435–112435. 9 indexed citations
10.
Wang, Y., Ching‐Yao Lai, Javier Gómez-Serrano, & Tristan Buckmaster. (2023). Asymptotic Self-Similar Blow-Up Profile for Three-Dimensional Axisymmetric Euler Equations Using Neural Networks. Physical Review Letters. 130(24). 244002–244002. 11 indexed citations
11.
Lin, Ning, et al.. (2022). Using Neural Networks to Predict Hurricane Storm Surge and to Assess the Sensitivity of Surge to Storm Characteristics. Journal of Geophysical Research Atmospheres. 127(24). 19 indexed citations
12.
MacAyeal, Douglas R., Luke Copland, Derek Mueller, et al.. (2022). Enigmatic surface rolls of the Ellesmere Ice Shelf. Journal of Glaciology. 1–12. 3 indexed citations
13.
Apul, Onur G., Mary Jo Kirisits, Subhabrata Dev, et al.. (2022). Symbiotic Engineering: A Novel Approach for Environmental Remediation. ACS ES&T Engineering. 2(4). 606–616. 3 indexed citations
14.
Buck, W. Roger & Ching‐Yao Lai. (2021). Flexural Control of Basal Crevasse Opening Under Ice Shelves. Geophysical Research Letters. 48(8). 10 indexed citations
15.
Shim, Suin, Sepideh Khodaparast, Ching‐Yao Lai, et al.. (2021). CO2-Driven diffusiophoresis for maintaining a bacteria-free surface. Soft Matter. 17(9). 2568–2576. 18 indexed citations
16.
Lai, Ching‐Yao, Laura A. Stevens, T. T. Creyts, et al.. (2021). Hydraulic transmissivity inferred from ice-sheet relaxation following Greenland supraglacial lake drainages. Nature Communications. 12(1). 3955–3955. 19 indexed citations
17.
Lai, Ching‐Yao, Jonathan Kingslake, Martin Wearing, et al.. (2020). Vulnerability of Antarctica’s ice shelves to meltwater-driven fracture. Nature. 584(7822). 574–578. 139 indexed citations
18.
Lai, Ching‐Yao, Jens Eggers, & Luc Deike. (2018). Bubble Bursting: Universal Cavity and Jet Profiles. Physical Review Letters. 121(14). 144501–144501. 72 indexed citations
19.
Lai, Ching‐Yao, Zhong Zheng, Emilie Dressaire, et al.. (2016). Elastic Relaxation of Fluid-Driven Cracks and the Resulting Backflow. Physical Review Letters. 117(26). 268001–268001. 24 indexed citations
20.
Lai, Ching‐Yao, Zhong Zheng, Emilie Dressaire, Jason Wexler, & Howard A. Stone. (2015). Experimental study on penny-shaped fluid-driven cracks in an elastic matrix. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 471(2182). 20150255–20150255. 39 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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