Rubao Lee

2.7k total citations · 1 hit paper
51 papers, 1.9k citations indexed

About

Rubao Lee is a scholar working on Computer Networks and Communications, Information Systems and Signal Processing. According to data from OpenAlex, Rubao Lee has authored 51 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Computer Networks and Communications, 27 papers in Information Systems and 18 papers in Signal Processing. Recurrent topics in Rubao Lee's work include Advanced Data Storage Technologies (27 papers), Cloud Computing and Resource Management (25 papers) and Advanced Database Systems and Queries (21 papers). Rubao Lee is often cited by papers focused on Advanced Data Storage Technologies (27 papers), Cloud Computing and Resource Management (25 papers) and Advanced Database Systems and Queries (21 papers). Rubao Lee collaborates with scholars based in United States, China and Japan. Rubao Lee's co-authors include Xiaodong Zhang, Xiaodong Zhang, Fusheng Wang, Feng Chen, Yin Huai, Joel Saltz, Yuan Yuan, Hoang Vo, Ablimit Aji and Qiaoling Liu and has published in prestigious journals such as IEEE Transactions on Computers, Proceedings of the VLDB Endowment and ACM SIGMETRICS Performance Evaluation Review.

In The Last Decade

Rubao Lee

47 papers receiving 1.8k citations

Hit Papers

align trajectories

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.

Hadoop GIS

2013 402 citations Fusheng Wang, Rubao Lee 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						Papers	Cites
Rubao Lee United States	22	1.4k	849	539	445	377	51	1.9k
Jens Dittrich Germany	19	1.4k 1.0×	1.3k 1.5×	376 0.7×	120 0.3×	259 0.7×	51	1.8k
Stefan Manegold Netherlands	25	1.7k 1.2×	667 0.8×	930 1.7×	299 0.7×	296 0.8×	78	2.1k
David Lomet United States	28	2.2k 1.5×	744 0.9×	878 1.6×	472 1.1×	206 0.5×	125	2.7k
Stratis D. Viglas United Kingdom	18	2.1k 1.4×	725 0.9×	1.1k 2.1×	447 1.0×	202 0.5×	45	2.7k
Andrew Fikes United States	5	2.8k 2.0×	2.2k 2.6×	405 0.8×	235 0.5×	320 0.8×	5	3.4k
Jeong-Hyon Hwang United States	15	1.5k 1.0×	701 0.8×	728 1.4×	74 0.2×	182 0.5×	30	1.8k
Shrideep Pallickara United States	20	1.1k 0.8×	758 0.9×	188 0.3×	115 0.3×	138 0.4×	123	1.6k
Kostas Tzoumas Germany	14	1.1k 0.8×	886 1.0×	354 0.7×	146 0.3×	297 0.8×	19	1.6k
Yin Huai United States	8	915 0.6×	785 0.9×	286 0.5×	126 0.3×	275 0.7×	11	1.3k
Niels Nes Netherlands	16	1.3k 0.9×	476 0.6×	607 1.1×	204 0.5×	223 0.6×	32	1.5k

Countries citing papers authored by Rubao Lee

Since Specialization

Citations

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

Fields of papers citing papers by Rubao Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rubao Lee

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

20 of 20 papers shown

1.

Lee, Rubao, et al.. (2025). LibRTS: A Spatial Indexing Library by Ray Tracing. 396–411.

2.

Xiao, Mengbai, et al.. (2024). UltraPrecise: A GPU-Based Framework for Arbitrary-Precision Arithmetic in Database Systems. 3837–3850. 1 indexed citations

3.

Zhang, Xiaodong & Rubao Lee. (2024). Data Management. Cambridge University Press eBooks. 2 indexed citations

4.

Wang, Fusheng, et al.. (2024). High-Performance Spatial Data Analytics: Systematic R&D for Scale-Out and Scale-Up Solutions from the Past to Now. Proceedings of the VLDB Endowment. 17(12). 4507–4520. 1 indexed citations

5.

Xiao, Mengbai, et al.. (2021). NestGPU: Nested Query Processing on GPU. 1008–1019. 11 indexed citations

6.

Lee, Rubao, et al.. (2021). The art of balance. Proceedings of the VLDB Endowment. 14(12). 2999–3013. 30 indexed citations

7.

Qin, An, et al.. (2019). DirectLoad: A Fast Web-Scale Index System Across Large Regional Centers. 1790–1801. 7 indexed citations

8.

Qin, An, et al.. (2017). Feisu: Fast Query Execution over Heterogeneous Data Sources on Large-Scale Clusters. 2000. 1173–1182. 2 indexed citations

9.

Yuan, Yuan, et al.. (2016). Spark-GPU: An accelerated in-memory data processing engine on clusters. IEEE Conference Proceedings. 2016. 283. 1 indexed citations

10.

Wang, Wenjuan, et al.. (2016). SparkArray: An Array-Based Scientific Data Management System Built on Apache Spark. 1–10. 6 indexed citations

11.

Liu, Taoying, et al.. (2016). A Case Study of Optimizing Big Data Analytical Stacks Using Structured Data Shuffling. 28. 91–100. 1 indexed citations

12.

Yuan, Yuan, et al.. (2016). Spark-GPU: An accelerated in-memory data processing engine on clusters. 273–283. 32 indexed citations

13.

Yuan, Yuan, Kaibo Wang, Rubao Lee, et al.. (2016). BCC. Proceedings of the VLDB Endowment. 9(6). 504–515. 32 indexed citations

14.

Zhang, Kai, Chen Feng, Xiaoning Ding, et al.. (2015). Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources. Journal of Computer Science and Technology. 30(4). 657–678. 5 indexed citations

15.

Luo, Tian, et al.. (2013). S-CAVE: effective SSD caching to improve virtual machine storage performance. International Conference on Parallel Architectures and Compilation Techniques. 103–112. 48 indexed citations

16.

Luo, Tian, et al.. (2013). Fairness-aware scheduling on single-ISA heterogeneous multi-cores. 177–188. 35 indexed citations

17.

Wang, Fusheng, Rubao Lee, Xiaodong Zhang, & Joel Saltz. (2011). Towards building high performance medical image management system for clinical trials. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7967(79670C). 79670C–79670C. 3 indexed citations

18.

Lee, Rubao, Xiaoning Ding, Feng Chen, Qingda Lu, & Xiaodong Zhang. (2009). MCC-DB. Proceedings of the VLDB Endowment. 2(1). 373–384. 29 indexed citations

19.

Lee, Rubao, et al.. (2007). Request Window: an approach to improve throughput of RDBMS-based data integration system by utilizing data sharing across concurrent distributed queries. Very Large Data Bases. 1219–1230. 15 indexed citations

20.

Lee, Rubao, et al.. (2007). Architectural characterization of XQuery workloads on modern processors. 1–12. 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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