Tingran Gao

421 total citations
18 papers, 218 citations indexed

About

Tingran Gao is a scholar working on Computational Theory and Mathematics, Geometry and Topology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Tingran Gao has authored 18 papers receiving a total of 218 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computational Theory and Mathematics, 5 papers in Geometry and Topology and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Tingran Gao's work include Morphological variations and asymmetry (5 papers), Topological and Geometric Data Analysis (4 papers) and Evolution and Paleontology Studies (3 papers). Tingran Gao is often cited by papers focused on Morphological variations and asymmetry (5 papers), Topological and Geometric Data Analysis (4 papers) and Evolution and Paleontology Studies (3 papers). Tingran Gao collaborates with scholars based in United States, United Kingdom and China. Tingran Gao's co-authors include Douglas Boyer, Ingrid Daubechies, Ingrid Daubechies, Shahar Z. Kovalsky, Callum F. Ross, Courtney P. Orsbon, Nicholas J. Gidmark, Sayan Mukherjee, Yue Lu and Gabriel Yapuncich and has published in prestigious journals such as PLoS ONE, Scientific Reports and Applied Mathematics and Computation.

In The Last Decade

Tingran Gao

18 papers receiving 209 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tingran Gao United States	11	68	45	45	39	28	18	218
Jesús Puente United States	5	61 0.9×	78 1.7×	130 2.9×	23 0.6×	20 0.7×	8	243
Arne Dür Austria	12	33 0.5×	27 0.6×	21 0.5×	48 1.2×	48 1.7×	31	760
A. Cicuttin Italy	11	15 0.2×	31 0.7×	6 0.1×	11 0.3×	14 0.5×	60	375
Megan Owen United States	8	35 0.5×	32 0.7×	55 1.2×	58 1.5×	3 0.1×	15	219
Michael J. Prentice United Kingdom	10	29 0.4×	5 0.1×	69 1.5×	5 0.1×	15 0.5×	16	340
E. H. Lockwood United Kingdom	4	33 0.5×	4 0.1×	35 0.8×	6 0.2×	7 0.3×	21	302
Torbjörn Lundh Sweden	12	15 0.2×	3 0.1×	26 0.6×	28 0.7×	30 1.1×	44	312
Jordan Hoffmann United States	7	17 0.3×	3 0.1×	7 0.2×	4 0.1×	11 0.4×	13	239
Anders Brun Sweden	11	201 3.0×	4 0.1×	2 0.0×	9 0.2×	16 0.6×	36	368

Countries citing papers authored by Tingran Gao

Since Specialization

Citations

This map shows the geographic impact of Tingran Gao'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 Tingran Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tingran Gao more than expected).

Fields of papers citing papers by Tingran Gao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tingran Gao. 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 Tingran Gao. The network helps show where Tingran Gao may publish in the future.

Co-authorship network of co-authors of Tingran Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Tingran Gao. A scholar is included among the top collaborators of Tingran Gao 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 Tingran Gao. Tingran Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Wang, Bruce, et al.. (2021). A statistical pipeline for identifying physical features that differentiate classes of 3D shapes. The Annals of Applied Statistics. 15(2). 12 indexed citations

Shan, Shan, et al.. (2021). Reconstructing dietary ecology of extinct strepsirrhines (Primates, Mammalia) with new approaches for characterizing and analyzing tooth shape. Paleobiology. 47(4). 612–631. 15 indexed citations

Fan, Yifeng, Tingran Gao, & Zhizhen Zhao. (2021). Representation theoretic patterns in multi-frequency class averaging for three-dimensional cryo-electron microscopy. Information and Inference A Journal of the IMA. 10(3). 723–771. 2 indexed citations

Orsbon, Courtney P., Nicholas J. Gidmark, Tingran Gao, & Callum F. Ross. (2020). XROMM and diceCT reveal a hydraulic mechanism of tongue base retraction in swallowing. Scientific Reports. 10(1). 8215–8215. 30 indexed citations

Gao, Tingran, et al.. (2020). Uniform-in-time weak error analysis for stochastic gradient descent algorithms via diffusion approximation. Communications in Mathematical Sciences. 18(1). 163–188. 4 indexed citations

Gao, Tingran, Shahar Z. Kovalsky, & Ingrid Daubechies. (2019). Gaussian Process Landmarking on Manifolds. SIAM Journal on Mathematics of Data Science. 1(1). 208–236. 17 indexed citations

Gao, Tingran, Shahar Z. Kovalsky, Douglas Boyer, & Ingrid Daubechies. (2019). Gaussian Process Landmarking for Three-Dimensional Geometric Morphometrics. SIAM Journal on Mathematics of Data Science. 1(1). 237–267. 16 indexed citations

Collins, Katie S., Stewart M. Edie, Tingran Gao, Rüdiger Bieler, & David Jablonski. (2019). Spatial filters of function and phylogeny determine morphological disparity with latitude. PLoS ONE. 14(8). e0221490–e0221490. 12 indexed citations

Gao, Tingran, Jacek Brodzki, & Sayan Mukherjee. (2019). The Geometry of Synchronization Problems and Learning Group Actions. Discrete & Computational Geometry. 65(1). 150–211. 5 indexed citations

10.

Fan, Yifeng, Tingran Gao, & Zhizhen Zhao. (2019). Unsupervised Co-Learning on $G$-Manifolds Across Irreducible Representations. Neural Information Processing Systems. 32. 9041–9053. 2 indexed citations

11.

Gao, Tingran, Shahab Asoodeh, Yi Huang, & James A. Evans. (2019). Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 3630–3637. 2 indexed citations

12.

Liu, Yunru, Tingran Gao, & Haizhao Yang. (2019). SelectNet: Learning to Sample from the Wild for Imbalanced Data Training. 193–206. 2 indexed citations

13.

Gao, Tingran. (2019). The diffusion geometry of fibre bundles: Horizontal diffusion maps. Applied and Computational Harmonic Analysis. 50. 147–215. 8 indexed citations

14.

Bajaj, Chandrajit, et al.. (2018). SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions.. PubMed. 80. 324–333. 10 indexed citations

15.

Gao, Tingran, Gabriel Yapuncich, Ingrid Daubechies, Sayan Mukherjee, & Douglas Boyer. (2017). Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation. The Anatomical Record. 301(4). 636–658. 25 indexed citations

16.

Vitek, Natasha, et al.. (2017). Semi‐supervised determination of pseudocryptic morphotypes using observer‐free characterizations of anatomical alignment and shape. Ecology and Evolution. 7(14). 5041–5055. 13 indexed citations

17.

Gao, Tingran, et al.. (2017). A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets. SIAM Journal on Imaging Sciences. 10(2). 711–750. 31 indexed citations

18.

Zhang, Liping, Soon‐Yi Wu, & Tingran Gao. (2009). Improved smoothing Newton methods for nonlinear complementarity problems. Applied Mathematics and Computation. 215(1). 324–332. 12 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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