Shuai Ding

768 total citations
11 papers, 508 citations indexed

About

Shuai Ding is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shuai Ding has authored 11 papers receiving a total of 508 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Signal Processing, 7 papers in Artificial Intelligence and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shuai Ding's work include Data Management and Algorithms (8 papers), Algorithms and Data Compression (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Shuai Ding is often cited by papers focused on Data Management and Algorithms (8 papers), Algorithms and Data Compression (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Shuai Ding collaborates with scholars based in United States and China. Shuai Ding's co-authors include Torsten Suel, Hao Yan, Josh Attenberg, Jing He, Xiaoming Li, Hongfei Yan, Honghua Li, Ping Tan, Zilong Dong and Siyu Zhu and has published in prestigious journals such as Informatica, arXiv (Cornell University) and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

In The Last Decade

Shuai Ding

11 papers receiving 479 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shuai Ding United States	8	293	287	251	188	142	11	508
Amer Aljaedi Saudi Arabia	12	170 0.6×	167 0.6×	74 0.3×	159 0.8×	184 1.3×	74	540
Vo Ngoc Anh Australia	11	451 1.5×	364 1.3×	313 1.2×	294 1.6×	148 1.0×	25	691
Vincent H. Berk United States	11	286 1.0×	333 1.2×	198 0.8×	90 0.5×	63 0.4×	22	446
Jianlin Feng China	9	141 0.5×	165 0.6×	216 0.9×	100 0.5×	283 2.0×	19	482
Frédéric Raynal France	11	145 0.5×	151 0.5×	176 0.7×	95 0.5×	195 1.4×	16	417
Darren Erik Vengroff United States	8	175 0.6×	266 0.9×	194 0.8×	50 0.3×	81 0.6×	17	448
Eric Sedlar United States	8	213 0.7×	456 1.6×	188 0.7×	160 0.9×	111 0.8×	12	551
Cheng Sheng Hong Kong	10	138 0.5×	204 0.7×	289 1.2×	110 0.6×	216 1.5×	18	481
Verónica Gil-Costa Argentina	10	103 0.4×	191 0.7×	100 0.4×	109 0.6×	89 0.6×	71	354

Countries citing papers authored by Shuai Ding

Since Specialization

Citations

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

Fields of papers citing papers by Shuai Ding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuai Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Shuai Ding. A scholar is included among the top collaborators of Shuai Ding 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 Shuai Ding. Shuai Ding 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:

11 of 11 papers shown

1.

Wang, Wenping, et al.. (2023). Integrity and Junkiness Failure Handling for Embedding-based Retrieval: A Case Study in Social Network Search. arXiv (Cornell University). 3250–3254. 5 indexed citations

2.

Ding, Shuai, et al.. (2021). Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 8890–8897. 25 indexed citations

3.

Fan, Wenjuan, et al.. (2016). A Novel Trust Inference Framework for Web-Based Scenarios Harnessed by Social Network and Web of Trust – a Heuristic Approach. Informatica. 27(2). 405–432. 3 indexed citations

4.

Ding, Shuai, et al.. (2012). Optimized top-k processing with global page scores on block-max indexes. 423–432. 25 indexed citations

5.

Ding, Shuai, Josh Attenberg, Ricardo Baeza‐Yates, & Torsten Suel. (2011). Batch query processing for web search engines. 137–146. 15 indexed citations

6.

Ding, Shuai & Torsten Suel. (2011). Faster top-k document retrieval using block-max indexes. 993–1002. 148 indexed citations

7.

Ding, Shuai, Sreenivas Gollapudi, Samuel Ieong, Krishnaram Kenthapadi, & Alexandros Ntoulas. (2011). Indexing strategies for graceful degradation of search quality. 575–584. 5 indexed citations

8.

Ding, Shuai, Josh Attenberg, & Torsten Suel. (2010). Scalable techniques for document identifier assignment in inverted indexes. 311–320. 30 indexed citations

9.

Yan, Hao, Shuai Ding, & Torsten Suel. (2009). Inverted index compression and query processing with optimized document ordering. 401–410. 171 indexed citations

10.

Yan, Hao, Shuai Ding, & Torsten Suel. (2009). Compressing term positions in web indexes. 147–154. 36 indexed citations

11.

Ding, Shuai, et al.. (2008). Using graphics processors for high-performance IR query processing. 1213–1214. 45 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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