Bei Wang

3.0k total citations
110 papers, 1.1k citations indexed

About

Bei Wang is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Bei Wang has authored 110 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Computational Theory and Mathematics, 48 papers in Computer Vision and Pattern Recognition and 17 papers in Artificial Intelligence. Recurrent topics in Bei Wang's work include Topological and Geometric Data Analysis (57 papers), Data Visualization and Analytics (35 papers) and Cell Image Analysis Techniques (14 papers). Bei Wang is often cited by papers focused on Topological and Geometric Data Analysis (57 papers), Data Visualization and Analytics (35 papers) and Cell Image Analysis Techniques (14 papers). Bei Wang collaborates with scholars based in United States, China and Sweden. Bei Wang's co-authors include Valerio Pascucci, Peer‐Timo Bremer, Shusen Liu, Dan Maljovec, Paul Rosen, Lin Yan, Ingrid Hotz, Mustafa Hajij, Carlos Scheidegger and Vivek Srikumar and has published in prestigious journals such as Nature Cell Biology, Journal of Lightwave Technology and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Bei Wang

94 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bei Wang United States	16	515	368	242	135	93	110	1.1k
Yusu Wang United States	25	461 0.9×	473 1.3×	105 0.4×	136 1.0×	302 3.2×	113	1.6k
Olivier Lézoray France	19	958 1.9×	113 0.3×	436 1.8×	112 0.8×	53 0.6×	95	1.5k
Joshua A. Levine United States	19	636 1.2×	189 0.5×	193 0.8×	59 0.4×	52 0.6×	69	1.6k
Gunther H. Weber United States	22	640 1.2×	353 1.0×	148 0.6×	227 1.7×	333 3.6×	79	1.5k
I. García Spain	20	188 0.4×	263 0.7×	267 1.1×	54 0.4×	135 1.5×	121	1.6k
Xin Jin China	23	1.1k 2.2×	91 0.2×	345 1.4×	59 0.4×	79 0.8×	166	1.7k
Attila Gyulassy United States	21	507 1.0×	540 1.5×	59 0.2×	224 1.7×	34 0.4×	38	1.1k
Robert van Liere Netherlands	22	713 1.4×	81 0.2×	142 0.6×	60 0.4×	106 1.1×	105	1.5k
Alexander Mordvintsev United States	10	547 1.1×	85 0.2×	778 3.2×	89 0.7×	68 0.7×	19	1.4k
Ludwig Schubert United States	11	374 0.7×	112 0.3×	738 3.0×	98 0.7×	46 0.5×	18	1.3k

Countries citing papers authored by Bei Wang

Since Specialization

Citations

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

Fields of papers citing papers by Bei Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bei Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Bei Wang. A scholar is included among the top collaborators of Bei 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 Bei Wang. Bei 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

Yan, Lin, et al.. (2024). Topological Characterization and Uncertainty Visualization of Atmospheric Rivers. Computer Graphics Forum. 43(3). 2 indexed citations

Rodgers, Peter, et al.. (2024). Generating Euler Diagrams Through Combinatorial Optimization. Computer Graphics Forum. 43(3).

Carr, Hamish, et al.. (2024). Distributed Augmentation, Hypersweeps, and Branch Decomposition of Contour Trees for Scientific Exploration. IEEE Transactions on Visualization and Computer Graphics. 31(1). 152–162.

Phillips, Jeff M., et al.. (2024). Fast Comparative Analysis of Merge Trees Using Locality Sensitive Hashing. IEEE Transactions on Visualization and Computer Graphics. 31(1). 141–151. 1 indexed citations

Wang, Bei, et al.. (2024). Labeled interleaving distance for Reeb graphs. 8(8). 2367–2399. 1 indexed citations

Yan, Lin, Paul Ullrich, Luke Van Roekel, Bei Wang, & Hanqi Guo. (2023). Multilevel Robustness for 2D Vector Field Feature Tracking, Selection and Comparison. Computer Graphics Forum. 42(6). 1 indexed citations

Srikumar, Vivek, et al.. (2023). TopoBERT: Exploring the topology of fine-tuned word representations. Information Visualization. 22(3). 186–208. 6 indexed citations

Rosen, Paul, Mustafa Hajij, & Bei Wang. (2023). Homology-Preserving Multi-Scale Graph Skeletonization Using Mapper on Graphs. 19. 10–20. 1 indexed citations

Wang, Bei, et al.. (2022). Uncertainty Visualization for Graph Coarsening. 2022 IEEE International Conference on Big Data (Big Data). 10. 2922–2931.

10.

Anderson, Lauren, Anders Ynnerman, Alexander Böck, et al.. (2021). Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth. Computer Graphics Forum. 40(3). 635–663. 7 indexed citations

11.

Li, Jingqiang, et al.. (2020). On characteristics of attention quality of controller based on k-means clustering. Zhongguo anquan kexue xuebao. 27(6). 13. 2 indexed citations

12.

Wang, Bei, et al.. (2019). Robust Extraction and Simplification of 2D Symmetric Tensor Field Topology. Computer Graphics Forum. 38(3). 337–349. 9 indexed citations

13.

Kerber, Michael, et al.. (2019). A kernel for multi-parameter persistent homology. IRIS UNIMORE (University of Modena and Reggio Emilia). 12 indexed citations

14.

Wang, Bei, et al.. (2019). TopoAct: Exploring the Shape of Activations in Deep Learning. arXiv (Cornell University). 2 indexed citations

15.

Hajij, Mustafa, Bei Wang, & Paul Rosen. (2018). MOG: Mapper on Graphs for Relationship Preserving Clustering. arXiv (Cornell University). 2 indexed citations

16.

Anderson, Jeffrey S., et al.. (2018). Topological Data Analysis of Functional MRI Connectivity in Time and Space Domains. Lecture notes in computer science. 11083. 67–77. 22 indexed citations

17.

Hajij, Mustafa, Bei Wang, Carlos Scheidegger, & Paul Rosen. (2017). Persistent Homology Guided Exploration of Time-Varying Graphs.. arXiv (Cornell University). 1 indexed citations

18.

Zhao, Shengmei, Peng Shi, & Bei Wang. (2011). Designs of Bhattacharyya Parameter in the Construction of Polar Codes. 1–4. 17 indexed citations

19.

Wang, Bei. (2008). Improved Medical Image Registration Algorithm Based on Maximization of Normalized Mutual Information.

20.

Bendich, Paul, Bei Wang, & Sayan Mukherjee. (1959). Local homology transfer and stratification learning. PubMed Central. 24(4). 1355–1370. 15 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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