Ji Sun

838 total citations
17 papers, 549 citations indexed

About

Ji Sun is a scholar working on Computer Networks and Communications, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Ji Sun has authored 17 papers receiving a total of 549 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Networks and Communications, 11 papers in Signal Processing and 8 papers in Artificial Intelligence. Recurrent topics in Ji Sun's work include Data Management and Algorithms (11 papers), Advanced Database Systems and Queries (10 papers) and Data Stream Mining Techniques (5 papers). Ji Sun is often cited by papers focused on Data Management and Algorithms (11 papers), Advanced Database Systems and Queries (10 papers) and Data Stream Mining Techniques (5 papers). Ji Sun collaborates with scholars based in China, Qatar and United States. Ji Sun's co-authors include Guoliang Li, Xuanhe Zhou, Chengliang Chai, Jianhua Feng, Yue Han, Nan Tang, Haitao Yuan, Jintao Zhang, Xiang Yu and Tianqing Wang and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment and Journal of Optimization Theory and Applications.

In The Last Decade

Ji Sun

16 papers receiving 544 citations

Peers

Ji Sun
Parimarjan Negi United States
Luis L. Perez United States
Xuanhe Zhou China
Niketan Pansare United States
Andreas Kipf Germany
Tyler Akidau United States
Jennie Duggan United States
Itaru Nishizawa United States
Vassilis Papadimos United States
Reza Akbarinia France
Parimarjan Negi United States
Ji Sun
Citations per year, relative to Ji Sun Ji Sun (= 1×) peers Parimarjan Negi

Countries citing papers authored by Ji Sun

Since Specialization
Citations

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

Fields of papers citing papers by Ji Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ji Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Ji Sun. A scholar is included among the top collaborators of Ji Sun 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 Ji Sun. Ji Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Sun, Ji, et al.. (2025). GaussDB-Vector: A Large-Scale Persistent Real-Time Vector Database for LLM Applications. Proceedings of the VLDB Endowment. 18(12). 4951–4963.
2.
Zhou, Xuanhe, Chengliang Chai, Guoliang Li, & Ji Sun. (2023). Database Meets Artificial Intelligence: A Survey (Extended Abstract). 3901–3902. 1 indexed citations
3.
Yu, X. D., Chengliang Chai, Xinning Zhang, et al.. (2022). AlphaQO: Robust Learned Query Optimizer. 12(1). 7–29. 1 indexed citations
4.
Han, Yue, Guoliang Li, Haitao Yuan, & Ji Sun. (2022). AutoView: An Autonomous Materialized View Management System with Encoder-Reducer. IEEE Transactions on Knowledge and Data Engineering. 1–1. 1 indexed citations
5.
Yue, Han, Guoliang Li, Haitao Yuan, & Ji Sun. (2021). An Autonomous Materialized View Management System with Deep Reinforcement Learning. 2159–2164. 22 indexed citations
6.
Sun, Ji, et al.. (2021). Learned cardinality estimation. Proceedings of the VLDB Endowment. 15(1). 85–97. 49 indexed citations
7.
Zhou, Xuanhe, Ji Sun, Xiang Yu, et al.. (2021). DBMind. Proceedings of the VLDB Endowment. 14(12). 2743–2746. 21 indexed citations
8.
Li, Guoliang, Xuanhe Zhou, Ji Sun, et al.. (2021). openGauss. Proceedings of the VLDB Endowment. 14(12). 3028–3042. 62 indexed citations
9.
Sun, Ji, Guoliang Li, & Nan Tang. (2021). Learned Cardinality Estimation for Similarity Queries. 1745–1757. 19 indexed citations
10.
Zhou, Xuanhe, Ji Sun, Guoliang Li, & Jianhua Feng. (2020). Query performance prediction for concurrent queries using graph embedding. Proceedings of the VLDB Endowment. 13(9). 1416–1428. 61 indexed citations
11.
Zhou, Xuanhe, Chengliang Chai, Guoliang Li, & Ji Sun. (2020). Database Meets Artificial Intelligence: A Survey. IEEE Transactions on Knowledge and Data Engineering. 34(3). 1096–1116. 96 indexed citations
12.
Yuan, Haitao, Guoliang Li, Ling Feng, Ji Sun, & Yue Han. (2020). Automatic View Generation with Deep Learning and Reinforcement Learning. 1501–1512. 45 indexed citations
13.
Sun, Ji & Guoliang Li. (2019). An end-to-end learning-based cost estimator. Proceedings of the VLDB Endowment. 13(3). 307–319. 137 indexed citations
14.
Sun, Ji, et al.. (2019). Balance-aware distributed string similarity-based query processing system. Proceedings of the VLDB Endowment. 12(9). 961–974. 10 indexed citations
15.
Sun, Ji, et al.. (2017). Dima. Proceedings of the VLDB Endowment. 10(12). 1925–1928. 18 indexed citations
16.
Zhang, Feng, et al.. (2013). Hydraulic Transient Prevention with Dipping Tube Hydropneumatic Tank. Applied Mechanics and Materials. 316-317. 762–765. 1 indexed citations
17.
Shen, Zong‐Yang, Qianchuan Zhao, Qing‐Shan Jia, & Ji Sun. (2008). Universal Alignment Probability Revisited. Journal of Optimization Theory and Applications. 141(2). 371–376. 5 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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