Yusu Wang

4.4k total citations
113 papers, 1.6k citations indexed

About

Yusu Wang is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Yusu Wang has authored 113 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Computational Theory and Mathematics, 33 papers in Computer Vision and Pattern Recognition and 26 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Yusu Wang's work include Topological and Geometric Data Analysis (45 papers), Computational Geometry and Mesh Generation (20 papers) and Data Management and Algorithms (12 papers). Yusu Wang is often cited by papers focused on Topological and Geometric Data Analysis (45 papers), Computational Geometry and Mesh Generation (20 papers) and Data Management and Algorithms (12 papers). Yusu Wang collaborates with scholars based in United States, China and Japan. Yusu Wang's co-authors include Jian Sun, Mikhail A. Belkin, Tamal K. Dey, Pankaj K. Agarwal, Herbert Edelsbrunner, Sariel Har-Peled, Facundo Mémoli, John Harer, Fengtao Fan and Maike Buchin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Bioinformatics.

In The Last Decade

Yusu Wang

108 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yusu Wang United States	25	473	461	357	340	302	113	1.6k
Vijay Natarajan India	24	798 1.7×	838 1.8×	195 0.5×	374 1.1×	118 0.4×	89	1.5k
Facundo Mémoli United States	22	818 1.7×	746 1.6×	680 1.9×	336 1.0×	212 0.7×	67	2.2k
Gunther H. Weber United States	22	353 0.7×	640 1.4×	140 0.4×	366 1.1×	333 1.1×	79	1.5k
Frédéric Cazals France	20	242 0.5×	455 1.0×	688 1.9×	615 1.8×	336 1.1×	82	1.8k
Frédéric Chazal France	23	1.2k 2.5×	663 1.4×	423 1.2×	375 1.1×	139 0.5×	63	1.9k
Joshua A. Levine United States	19	189 0.4×	636 1.4×	477 1.3×	528 1.6×	52 0.2×	69	1.6k
Steve Oudot France	16	853 1.8×	311 0.7×	225 0.6×	253 0.7×	99 0.3×	50	1.3k
David Letscher United States	13	332 0.7×	220 0.5×	106 0.3×	111 0.3×	717 2.4×	33	1.4k
Bei Wang United States	16	368 0.8×	515 1.1×	34 0.1×	92 0.3×	93 0.3×	110	1.1k
Olivier Lézoray France	19	113 0.2×	958 2.1×	207 0.6×	109 0.3×	53 0.2×	95	1.5k

Countries citing papers authored by Yusu Wang

Since Specialization

Citations

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

Fields of papers citing papers by Yusu Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yusu Wang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Sun, Liang, et al.. (2025). Substitution and coordination effects of boron in Fe C and Fe N C single-atom catalysts for ORR: A DFT study. Computational and Theoretical Chemistry. 1248. 115192–115192. 5 indexed citations

Kahng, Andrew B., Arya Mazumdar, J. Reeves, & Yusu Wang. (2024). The TILOS AI Institute: Integrating optimization and AI for chip design, networks, and robotics. AI Magazine. 45(1). 54–60.

Wang, Yusu. (2023). Study on the Development of Rural E-commerce Logistics “Last Kilometer” Awareness Based on the Background of Rural Revitalization. 4(3). p186–p186.

Clark, Aurora E., Henry Adams, Rigoberto Hernandez, et al.. (2021). The Middle Science: Traversing Scale In Complex Many-Body Systems. ACS Central Science. 7(8). 1271–1287. 18 indexed citations

Zhao, Qi, et al.. (2021). NN-Baker: A Neural-network Infused Algorithmic Framework for Optimization Problems on Geometric Intersection Graphs. Neural Information Processing Systems. 34. 2 indexed citations

Kim, Woojin, et al.. (2020). Elder-Rule-Staircodes for Augmented Metric Spaces. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations

Banerjee, Samik, Dingkang Wang, Xu Li, et al.. (2020). Semantic segmentation of microscopic neuroanatomical data by combining topological priors with encoder–decoder deep networks. Nature Machine Intelligence. 2(10). 585–594. 21 indexed citations

Zhao, Qi, Ze Ye, Chao Chen, & Yusu Wang. (2020). Persistence Enhanced Graph Neural Network. International Conference on Artificial Intelligence and Statistics. 2896–2906. 4 indexed citations

Zhao, Qi & Yusu Wang. (2019). Learning metrics for persistence-based summaries and applications for graph classification. arXiv (Cornell University). 32. 9855–9866. 10 indexed citations

10.

Wang, Yusu, et al.. (2019). FPT-Algorithms for Computing Gromov-Hausdorff and Interleaving Distances Between Trees. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 14. 3 indexed citations

11.

Belkin, Mikhail A., et al.. (2018). Unperturbed: spectral analysis beyond Davis-Kahan. 321–358. 10 indexed citations

12.

Wen, Xin, et al.. (2018). Study on the Preparation of Plasma-Modified Fly Ash Catalyst and Its De–NOX Mechanism. Materials. 11(6). 1047–1047. 12 indexed citations

13.

Quadrianto, Novi, et al.. (2017). Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data. Sussex Research Online (University of Sussex). 2622–2631. 6 indexed citations

14.

Dey, Tamal K., Fengtao Fan, & Yusu Wang. (2014). Dimension Detection with Local Homology.. arXiv (Cornell University). 1 indexed citations

15.

Belkin, Mikhail, et al.. (2014). Learning with Fredholm Kernels. Neural Information Processing Systems. 27. 2951–2959. 7 indexed citations

16.

Sun, Hong, Ahmet Saçan, Hakan Ferhatosmanoğlu, & Yusu Wang. (2012). Smolign: A Spatial Motifs-Based Protein Multiple Structural Alignment Method. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 9(1). 249–261. 29 indexed citations

17.

Belkin, Mikhail, et al.. (2012). Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries. Conference on Learning Theory. 10 indexed citations

18.

Belkin, Mikhail A., et al.. (2011). Data Skeletonization via Reeb Graphs. Neural Information Processing Systems. 24. 837–845. 31 indexed citations

19.

Buchin, Kevin, Maike Buchin, & Yusu Wang. (2009). Exact algorithms for partial curve matching via the Fréchet distance. Symposium on Discrete Algorithms. 645–654. 29 indexed citations

20.

Agarwal, Pankaj K., et al.. (2005). Lower bound for sparse Euclidean spanners. Symposium on Discrete Algorithms. 670–671. 10 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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