Dong Su

2.1k total citations
12 papers, 622 citations indexed

About

Dong Su is a scholar working on Artificial Intelligence, Sociology and Political Science and Computer Science Applications. According to data from OpenAlex, Dong Su has authored 12 papers receiving a total of 622 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 4 papers in Sociology and Political Science and 3 papers in Computer Science Applications. Recurrent topics in Dong Su's work include Privacy-Preserving Technologies in Data (10 papers), Cryptography and Data Security (6 papers) and Privacy, Security, and Data Protection (4 papers). Dong Su is often cited by papers focused on Privacy-Preserving Technologies in Data (10 papers), Cryptography and Data Security (6 papers) and Privacy, Security, and Data Protection (4 papers). Dong Su collaborates with scholars based in United States, China and Singapore. Dong Su's co-authors include Ninghui Li, Wahbeh Qardaji, Min Lyu, Jianneng Cao, Wei‐Ning Yang, Ninghui Li, Elisa Bertino, Hongxia Jin, Yi Wu and Ian Molloy and has published in prestigious journals such as Photogrammetric Engineering & Remote Sensing, Proceedings of the VLDB Endowment and The VLDB Journal.

In The Last Decade

Dong Su

12 papers receiving 601 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dong Su United States	10	598	207	116	70	54	12	622
Ninghui Li United States	11	540 0.9×	223 1.1×	107 0.9×	72 1.0×	58 1.1×	24	621
Jordi Soria-Comas Spain	12	470 0.8×	211 1.0×	93 0.8×	56 0.8×	52 1.0×	20	505
Wahbeh Qardaji United States	9	698 1.2×	265 1.3×	170 1.5×	92 1.3×	138 2.6×	12	787
Entong Shen United States	6	295 0.5×	82 0.4×	97 0.8×	43 0.6×	55 1.0×	8	376
Junbum Shin South Korea	8	336 0.6×	112 0.5×	44 0.4×	206 2.9×	31 0.6×	12	400
Huadi Zheng Hong Kong	8	281 0.5×	63 0.3×	67 0.6×	29 0.4×	54 1.0×	15	327
Hai Liu China	11	275 0.5×	97 0.5×	32 0.3×	53 0.8×	57 1.1×	48	371
Geetha Jagannathan United States	7	428 0.7×	75 0.4×	39 0.3×	94 1.3×	23 0.4×	11	485
Ali Khoshgozaran United States	9	636 1.1×	217 1.0×	173 1.5×	57 0.8×	163 3.0×	10	715

Countries citing papers authored by Dong Su

Since Specialization

Citations

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

Fields of papers citing papers by Dong Su

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dong Su

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

12 of 12 papers shown

1.

Wang, Tianhao, Zhikun Zhang, Dong Su, et al.. (2021). Continuous Release of Data Streams under both Centralized and Local Differential Privacy. 1237–1253. 37 indexed citations

2.

Ka, Zhang, et al.. (2020). Building Extraction from High-Resolution Remote Sensing Images Based on GrabCut with Automatic Selection of Foreground and Background Samples. Photogrammetric Engineering & Remote Sensing. 86(4). 235–245. 4 indexed citations

3.

Lee, Taesung, Ben Edwards, Ian Molloy, & Dong Su. (2019). Defending Against Neural Network Model Stealing Attacks Using Deceptive Perturbations. 43–49. 53 indexed citations

4.

Gu, Zhongshu, Heqing Huang, Jialong Zhang, et al.. (2018). YerbaBuena: Securing Deep Learning Inference Data via Enclave-based Ternary Model Partitioning. arXiv (Cornell University). 9 indexed citations

5.

Su, Dong, Jianneng Cao, Ninghui Li, & Min Lyu. (2018). PrivPfC: differentially private data publication for classification. The VLDB Journal. 27(2). 201–223. 14 indexed citations

6.

Lyu, Min, Dong Su, & Ninghui Li. (2017). Understanding the sparse vector technique for differential privacy. Proceedings of the VLDB Endowment. 10(6). 637–648. 70 indexed citations

7.

Su, Dong, Jianneng Cao, Ninghui Li, et al.. (2017). Differentially Private K-Means Clustering and a Hybrid Approach to Private Optimization. ACM Transactions on Privacy and Security. 20(4). 1–33. 30 indexed citations

8.

Su, Dong, Jianneng Cao, Ninghui Li, Elisa Bertino, & Hongxia Jin. (2016). Differentially Private K-Means Clustering. 26–37. 73 indexed citations

9.

Li, Ninghui, Min Lyu, Dong Su, & Wei‐Ning Yang. (2016). Differential Privacy: From Theory to Practice. 8(4). 1–138. 83 indexed citations

10.

Li, Ninghui, Wahbeh Qardaji, Dong Su, Yi Wu, & Wei‐Ning Yang. (2013). Membership privacy. 889–900. 85 indexed citations

11.

Li, Ninghui, Wahbeh Qardaji, Dong Su, & Jianneng Cao. (2012). PrivBasis. Proceedings of the VLDB Endowment. 5(11). 1340–1351. 106 indexed citations

12.

Li, Ninghui, Wahbeh Qardaji, & Dong Su. (2011). Provably Private Data Anonymization: Or, k-Anonymity Meets Differential Privacy. 58 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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