Kesheng Wu

8.4k total citations
242 papers, 5.1k citations indexed

About

Kesheng Wu is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Kesheng Wu has authored 242 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 122 papers in Computer Networks and Communications, 70 papers in Artificial Intelligence and 54 papers in Signal Processing. Recurrent topics in Kesheng Wu's work include Advanced Data Storage Technologies (64 papers), Advanced Database Systems and Queries (43 papers) and Distributed and Parallel Computing Systems (42 papers). Kesheng Wu is often cited by papers focused on Advanced Data Storage Technologies (64 papers), Advanced Database Systems and Queries (43 papers) and Distributed and Parallel Computing Systems (42 papers). Kesheng Wu collaborates with scholars based in United States, South Korea and China. Kesheng Wu's co-authors include Arie Shoshani, Ekow Otoo, Yousef Saad, Horst D. Simon, James R. Chelikowsky, Kenji Suzuki, N. Troullier, Alex Sim, Suren Byna and Kurt Stockinger and has published in prestigious journals such as SHILAP Revista de lepidopterología, Physical review. B, Condensed matter and Journal of Computational Physics.

In The Last Decade

Kesheng Wu

225 papers receiving 4.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kesheng Wu United States 35 1.6k 987 814 758 696 242 5.1k
Matteo Frigo United States 20 2.6k 1.6× 998 1.0× 835 1.0× 704 0.9× 607 0.9× 43 7.4k
Ping Guo China 37 601 0.4× 869 0.9× 935 1.1× 279 0.4× 231 0.3× 521 6.5k
Ming Li China 39 941 0.6× 1.2k 1.2× 1.1k 1.4× 160 0.2× 579 0.8× 450 7.9k
Richard Hanson United States 19 916 0.6× 1.0k 1.1× 791 1.0× 545 0.7× 585 0.8× 56 10.0k
Asok Ray United States 43 1.6k 1.0× 1.5k 1.5× 391 0.5× 937 1.2× 567 0.8× 678 10.0k
Peer‐Timo Bremer United States 38 628 0.4× 583 0.6× 2.0k 2.4× 214 0.3× 348 0.5× 198 4.8k
Michael T. Heath United States 31 1.2k 0.8× 668 0.7× 817 1.0× 265 0.3× 212 0.3× 96 6.7k
Richard P. Brent Australia 32 956 0.6× 1.7k 1.7× 555 0.7× 337 0.4× 535 0.8× 193 7.3k
John Nickolls United States 8 1.6k 1.0× 756 0.8× 817 1.0× 131 0.2× 221 0.3× 15 4.3k
George Cybenko United States 30 2.3k 1.4× 5.3k 5.4× 1.3k 1.5× 321 0.4× 1.0k 1.5× 151 12.9k

Countries citing papers authored by Kesheng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Kesheng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kesheng Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Kesheng Wu. A scholar is included among the top collaborators of Kesheng Wu 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 Kesheng Wu. Kesheng Wu 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.
Balaprakash, Prasanna, Franck Cappello, Ewa Deelman, et al.. (2025). SWARM: Reimagining scientific workflow management systems in a distributed world. The International Journal of High Performance Computing Applications. 39(5). 692–712. 2 indexed citations
2.
Eisenhauer, Greg, Norbert Podhorszki, Ana Gainaru, et al.. (2025). HPC I/O innovations in the exascale era. The International Journal of High Performance Computing Applications. 39(4). 594–612. 1 indexed citations
3.
Dong, Bin, Kesheng Wu, & Suren Byna. (2024). The Art of Sparsity: Mastering High-Dimensional Tensor Storage. 4. 439–446.
4.
Wu, Kesheng, et al.. (2024). Understanding Data Access Patterns for dCache System. SHILAP Revista de lepidopterología. 295. 1053–1053. 1 indexed citations
5.
Sim, Alex, et al.. (2023). Leveraging History to Predict Infrequent Abnormal Transfers in Distributed Workflows. Sensors. 23(12). 5485–5485.
6.
Kim, Jinoh, et al.. (2022). Enhancing IoT anomaly detection performance for federated learning. Digital Communications and Networks. 8(3). 314–323. 41 indexed citations
7.
Dong, Bin, et al.. (2020). DASSA: Parallel DAS Data Storage and Analysis for Subsurface Event Detection. 254–263. 10 indexed citations
8.
Ghosal, Dipak, et al.. (2020). A Deep Deterministic Policy Gradient Based Network Scheduler For Deadline-Driven Data Transfers. eScholarship (California Digital Library). 253–261. 7 indexed citations
9.
Sim, Alex, et al.. (2016). Machine learning based job status prediction in scientific clusters. eScholarship (California Digital Library). 44–53. 9 indexed citations
10.
Pugmire, David, James Kress, Scott Klasky, et al.. (2016). Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows. eScholarship (California Digital Library). 1007–1013. 5 indexed citations
11.
Byna, Suren, Jerry Chou, Oliver Rübel, et al.. (2012). Parallel I/O, analysis, and visualization of a trillion particle simulation. IEEE International Conference on High Performance Computing, Data, and Analytics. 1–12. 49 indexed citations
12.
Reiss, Frederick, Kurt Stockinger, Kesheng Wu, Arie Shoshani, & Joseph M. Hellerstein. (2007). Efficient Analysis of Live and Historical Streaming Data and its Application to Cybersecurity. University of North Texas Digital Library (University of North Texas). 3 indexed citations
13.
Wu, Kesheng, Ekow Otoo, & Arie Shoshani. (2005). Optimizing connected component labeling algorithms. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5747. 1965–1965. 146 indexed citations
14.
Wu, Kesheng, Ekow Otoo, & Arie Shoshani. (2004). An efficient compression scheme for bitmap indices. eScholarship (California Digital Library). 3 indexed citations
15.
Rotem, Doron, Kurt Stockinger, & Kesheng Wu. (2004). Efficient binning for bitmap indices on high-cardinality attributes. eScholarship (California Digital Library).
16.
Wu, Kesheng, Wendy S. Koegler, Jacqueline Chen, & Arie Shoshani. (2003). Using bitmap index for interactive exploration of large datasets. University of North Texas Digital Library (University of North Texas). 1 indexed citations
17.
Wu, Kesheng, Ekow Otoo, & Arie Shoshani. (2001). Compressed bitmap indices for efficient query processing. eScholarship (California Digital Library). 2 indexed citations
18.
Wu, Kesheng, Yousef Saad, & Andreas Stathopoulos. (1998). Inexact newton preconditioning techniques for large symmetric eigenvalue problems. ETNA - Electronic Transactions on Numerical Analysis. 7. 202–214. 25 indexed citations
19.
Wu, Kesheng. (1997). Preconditioned techniques for large eigenvalue problems. Clinical Endoscopy. 55(6). 801–809. 4 indexed citations
20.
Saad, Yousef, Kesheng Wu, & Serge G. Petiton. (1993). Sparse Matrix Computations on the CM-5.. PPSC. 414–420. 4 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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