Sai Wu

3.6k total citations · 1 hit paper
123 papers, 2.2k citations indexed

About

Sai Wu is a scholar working on Computer Networks and Communications, Information Systems and Signal Processing. According to data from OpenAlex, Sai Wu has authored 123 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Computer Networks and Communications, 33 papers in Information Systems and 32 papers in Signal Processing. Recurrent topics in Sai Wu's work include Data Management and Algorithms (32 papers), Cloud Computing and Resource Management (23 papers) and Advanced Database Systems and Queries (19 papers). Sai Wu is often cited by papers focused on Data Management and Algorithms (32 papers), Cloud Computing and Resource Management (23 papers) and Advanced Database Systems and Queries (19 papers). Sai Wu collaborates with scholars based in China, Singapore and United States. Sai Wu's co-authors include Beng Chin Ooi, Dawei Jiang, Lei Shi, Kian‐Lee Tan, Dongxiang Zhang, Gang Chen, Feng Li, Chun Chen, Jianzhong Li and Yanyan Shen and has published in prestigious journals such as Oncogene, PLoS Biology and Expert Systems with Applications.

In The Last Decade

Sai Wu

111 papers receiving 2.1k citations

Hit Papers

The performance of MapReduce 2010 2026 2015 2020 2010 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The performance of MapReduce
    2010 278 citations Dawei Jiang, Beng Chin Ooi et al. Proceedings of the VLDB Endowment profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sai Wu China 24 1.1k 1.1k 654 578 468 123 2.2k
Yuanyuan Tian United States 20 1.0k 0.9× 984 0.9× 954 1.5× 573 1.0× 1.0k 2.1× 57 2.4k
Anish Das Sarma United States 26 1.0k 0.9× 839 0.8× 1.1k 1.7× 756 1.3× 306 0.7× 47 2.2k
Xiaofeng Meng China 25 720 0.6× 753 0.7× 1.3k 2.0× 462 0.8× 170 0.4× 206 2.2k
Shuai Ma China 25 835 0.7× 677 0.6× 1.2k 1.8× 616 1.1× 655 1.4× 101 2.3k
Neoklis Polyzotis United States 33 1.4k 1.3× 927 0.9× 1.4k 2.1× 1.0k 1.8× 436 0.9× 93 3.0k
Bin Yao China 27 1.7k 1.5× 1.3k 1.2× 794 1.2× 770 1.3× 397 0.8× 105 3.2k
Emanuele Della Valle Italy 20 677 0.6× 449 0.4× 960 1.5× 442 0.8× 214 0.5× 108 1.5k
Sen Su China 28 2.0k 1.7× 1.3k 1.2× 1.1k 1.7× 153 0.3× 199 0.4× 202 3.3k
Ioana Manolescu France 21 1.4k 1.2× 800 0.8× 1.3k 2.0× 906 1.6× 189 0.4× 103 2.2k
Cuiping Li China 23 358 0.3× 684 0.7× 1.2k 1.8× 254 0.4× 291 0.6× 120 2.1k

Countries citing papers authored by Sai Wu

Since Specialization
Citations

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

Fields of papers citing papers by Sai Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sai Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Sai Wu. A scholar is included among the top collaborators of Sai 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 Sai Wu. Sai 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.
Shi, Meng, et al.. (2025). A Quantum Framework for Combinatorial Optimization Problem over Graphs. Data Science and Engineering. 10(2). 246–257. 2 indexed citations
2.
Wang, Rui, et al.. (2025). A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges. IEEE Transactions on Knowledge and Data Engineering. 38(1). 26–46. 3 indexed citations
3.
Liu, Jinghui, Xinyi Wang, Daheng He, et al.. (2025). Therapeutic targeting of the p300/CBP bromodomain enhances the efficacy of immune checkpoint blockade therapy. Oncogene. 44(28). 2386–2395. 4 indexed citations
4.
Wu, Sai, et al.. (2025). Serine phosphorylation of protein arginine methyltransferase Hmt1 is critical for controlling its protein levels. The International Journal of Biochemistry & Cell Biology. 185. 106790–106790.
5.
Shou, Lidan, et al.. (2024). FL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of Negative Federated Learning. Data Science and Engineering. 9(2). 204–219.
6.
Wu, Sai, et al.. (2024). QueryArtisan: Generating Data Manipulation Codes for Ad-hoc Analysis in Data Lakes. Proceedings of the VLDB Endowment. 18(2). 108–116.
7.
Kong, Yifan, Jinpeng Liu, Sai Wu, et al.. (2024). Single-cell analysis identifies PLK1 as a driver of immunosuppressive tumor microenvironment in LUAD. PLoS Genetics. 20(6). e1011309–e1011309. 6 indexed citations
8.
Wang, Yang, et al.. (2024). Against Jamming Attack in Wireless Communication Networks: A Reinforcement Learning Approach. Electronics. 13(7). 1209–1209. 2 indexed citations
9.
Wu, Sai, et al.. (2023). Text Labels Classification Model based on BERT Algorithm. 329–332.
10.
Lu, Jiaheng, et al.. (2022). A Survey on Mapping Semi-Structured Data and Graph Data to Relational Data. ACM Computing Surveys. 55(10). 1–38. 7 indexed citations
11.
Wu, Sai, et al.. (2022). Predictive value of ultrasonic features and microscopic extrathyroidal extension in the recurrence of PTC. European Journal of Radiology. 157. 110518–110518. 5 indexed citations
12.
Zhang, Dongxiang, et al.. (2020). Multi-Context Attention for Entity Matching. 2634–2640. 30 indexed citations
13.
Wu, Sai, et al.. (2019). NEIST: A Neural-Enhanced Index for Spatio-Temporal Queries. IEEE Transactions on Knowledge and Data Engineering. 33(4). 1659–1673. 4 indexed citations
14.
Li, Zhi, Yue Ma, Jie Tong, & Sai Wu. (2018). A Base Station Location Planning Method Based on Artificial Bee Colony Algorithm. 32. 252–256. 1 indexed citations
15.
Wu, Sai, et al.. (2017). CSIR4G: An effective and efficient cross-scenario image retrieval model for glasses. Information Sciences. 417. 310–327. 2 indexed citations
16.
Wu, Sai, Gang Chen, Ke Chen, Feng Li, & Lidan Shou. (2015). HM: A Column-Oriented MapReduce System on Hybrid Storage. IEEE Transactions on Knowledge and Data Engineering. 27(12). 3304–3317. 6 indexed citations
17.
Shou, Lidan & Sai Wu. (2013). Supporting Efficient Social Media Search in Cyber-Physical Web.. IEEE Data(base) Engineering Bulletin. 36. 83–90.
18.
Chen, Gang, Ke Chen, Dawei Jiang, et al.. (2012). E3: an Elastic Execution Engine for Scalable Data Processing. Journal of Information Processing. 20(1). 65–76. 8 indexed citations
19.
Wu, Sai & Kun‐Lung Wu. (2009). An Indexing Framework for Efficient Retrieval on the Cloud.. IEEE Data(base) Engineering Bulletin. 32. 75–82. 26 indexed citations
20.
Yeung, K.W., Chandan Kumar Chakrabarty, & Sai Wu. (1994). Discussion of using artificial neural nets to identify the well-test interpretation model. Proceedings of the Royal Society of Medicine. 30(7). 922–922. 1 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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