Jinzhu Gao

1.6k total citations · 1 hit paper
45 papers, 1.1k citations indexed

About

Jinzhu Gao is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computer Networks and Communications. According to data from OpenAlex, Jinzhu Gao has authored 45 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 17 papers in Computer Graphics and Computer-Aided Design and 10 papers in Computer Networks and Communications. Recurrent topics in Jinzhu Gao's work include Computer Graphics and Visualization Techniques (17 papers), Data Visualization and Analytics (15 papers) and Advanced Vision and Imaging (10 papers). Jinzhu Gao is often cited by papers focused on Computer Graphics and Visualization Techniques (17 papers), Data Visualization and Analytics (15 papers) and Advanced Vision and Imaging (10 papers). Jinzhu Gao collaborates with scholars based in United States, China and Canada. Jinzhu Gao's co-authors include Zhong Ming, Weipeng Cao, Xizhao Wang, Han‐Wei Shen, Paixian Fu, Hongwei Liu, Dianzhong Li, Xiaohui Cui, Thomas E. Potok and Jian Huang and has published in prestigious journals such as Nature Materials, Neurocomputing and IEEE Transactions on Computers.

In The Last Decade

Jinzhu Gao

42 papers receiving 1.1k 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.

A review on neural networks with random weights

2017 351 citations Weipeng Cao, Xizhao Wang et al. Neurocomputing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jinzhu Gao United States	17	341	301	253	194	186	45	1.1k
Xiaojuan Ban China	17	315 0.9×	447 1.5×	132 0.5×	107 0.6×	30 0.2×	142	1.3k
Weiqing Li China	15	291 0.9×	186 0.6×	76 0.3×	72 0.4×	35 0.2×	116	962
Lingfeng Yang China	13	155 0.5×	328 1.1×	65 0.3×	39 0.2×	115 0.6×	32	801
Zhang Li China	16	108 0.3×	362 1.2×	281 1.1×	166 0.9×	23 0.1×	189	1.1k
Guangrun Wang China	21	441 1.3×	1.2k 3.8×	167 0.7×	98 0.5×	14 0.1×	42	1.8k
Mingyuan Zhang China	17	355 1.0×	605 2.0×	74 0.3×	48 0.2×	45 0.2×	49	1.2k
Hitoshi Matsubara Japan	17	454 1.3×	268 0.9×	162 0.6×	95 0.5×	9 0.0×	107	1.2k
Goran Konjevod United States	21	113 0.3×	82 0.3×	278 1.1×	38 0.2×	79 0.4×	49	1.5k
Yunfeng Zhang Singapore	24	118 0.3×	235 0.8×	353 1.4×	31 0.2×	19 0.1×	80	1.6k

Countries citing papers authored by Jinzhu Gao

Since Specialization

Citations

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

Fields of papers citing papers by Jinzhu Gao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinzhu Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Jinzhu Gao. A scholar is included among the top collaborators of Jinzhu Gao 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 Jinzhu Gao. Jinzhu Gao 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.

Wang, Pei, Xing‐Qiu Chen, Paixian Fu, et al.. (2022). Low-oxygen rare earth steels. Nature Materials. 21(10). 1137–1143. 116 indexed citations

2.

Gao, Yi, et al.. (2018). Adaptive UPF Based Interacting Multiple Model Algorithm for Integrated Navigation. 18. 248–252. 1 indexed citations

3.

Cao, Weipeng, Jinzhu Gao, Zhong Ming, & Shubin Cai. (2017). Some Tricks in Parameter Selection for Extreme Learning Machine. IOP Conference Series Materials Science and Engineering. 261. 12002–12002. 28 indexed citations

4.

Cao, Weipeng, Xizhao Wang, Zhong Ming, & Jinzhu Gao. (2017). A review on neural networks with random weights. Neurocomputing. 275. 278–287. 351 indexed citations breakdown →

5.

Zhu, Kai, et al.. (2013). Similarity-based 3-D atmospheric nucleation data visualization and analysis. Tsinghua Science & Technology. 18(2). 137–144. 1 indexed citations

6.

Zhu, Kai, et al.. (2011). Application of Evolutionary Neural Networks for Well-logging Recognition in Petroleum Reservoir. Scholarly Commons (University of the Pacific). 2. 362–366. 1 indexed citations

7.

Zhu, Kai, et al.. (2011). Web-based Atmospheric Nucleation Data Management and Visualization. Scholarly Commons (University of the Pacific). 127–131. 2 indexed citations

8.

Zhu, Kai, et al.. (2011). Hybrid Genetic Algorithm for Cloud Computing Applications. Scholarly Commons (University of the Pacific). 182–187. 65 indexed citations

9.

Gao, Jinzhu & Jace Hargıs. (2010). Promoting Technology-Assisted Active Learning in Computer Science Education.. 10(2). 81–93. 15 indexed citations

10.

Gao, Jinzhu. (2010). Developing a web-based collaborative research environment for undergraduates. Scholarly Commons (University of the Pacific). 26(2). 39–46.

11.

Zhou, Yuyu, et al.. (2009). Web-Based Visualization of Atmospheric Nucleation Processes for Mobile Embedded Clients. Scholarly Commons (University of the Pacific). 12. 1–6. 1 indexed citations

12.

Shen, Han‐Wei, et al.. (2008). Interactive Exploration of Remote Isosurfaces with Point-Based Non-Photorealistic Rendering. Scholarly Commons (University of the Pacific). 25–32. 6 indexed citations

13.

Huang, Jian, et al.. (2007). Dynamic Sharing of Large-Scale Visualization. IEEE Computer Graphics and Applications. 27(1). 20–25. 3 indexed citations

14.

Huang, Jian, et al.. (2007). A Multi-Level Cache Model for Run-Time Optimization of Remote Visualization. IEEE Transactions on Visualization and Computer Graphics. 13(5). 991–1003. 10 indexed citations

15.

Huang, Jian, et al.. (2007). Scalable data servers for large multivariate volume visualization.. PubMed. 12(5). 1291–8. 15 indexed citations

16.

Gao, Jinzhu, Jian Huang, Christopher R. Johnson, Scott Atchley, & J.A. Kohl. (2006). Distributed Data Management for Large Volume Visualization. 183–189. 9 indexed citations

17.

Wang, Chaoli, Jinzhu Gao, Liya Li, & Han‐Wei Shen. (2005). A multiresolution volume rendering framework for large-scale time-varying data visualization. 11–223. 16 indexed citations

18.

Wang, Chaoli, Jinzhu Gao, & Han‐Wei Shen. (2004). Parallel multiresolution volume rendering of large data sets with error-guided load balancing. 23–30. 22 indexed citations

19.

Gao, Jinzhu & Han‐Wei Shen. (2002). Parallel view-dependent isosurface extraction using multi-pass occlusion culling. Scholarly Commons (University of the Pacific). 67–152. 17 indexed citations

20.

Gao, Jinzhu, et al.. (2001). Parallel View Dependent Isosurface Extraction for Large Scale Data Visualization.. Scholarly Commons (University of the Pacific). 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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