Gao Jun

588 total citations · 1 hit paper
52 papers, 361 citations indexed

About

Gao Jun is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Gao Jun has authored 52 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Automotive Engineering, 10 papers in Computer Vision and Pattern Recognition and 8 papers in Artificial Intelligence. Recurrent topics in Gao Jun's work include Autonomous Vehicle Technology and Safety (14 papers), Traffic Prediction and Management Techniques (8 papers) and Video Surveillance and Tracking Methods (6 papers). Gao Jun is often cited by papers focused on Autonomous Vehicle Technology and Safety (14 papers), Traffic Prediction and Management Techniques (8 papers) and Video Surveillance and Tracking Methods (6 papers). Gao Jun collaborates with scholars based in China, United States and United Kingdom. Gao Jun's co-authors include Yi Lu Murphey, Liudi Jiang, Jinghua Tang, David Moser, Michael McGrath, Saeed Zahedi, Dan L. Bader, Man Deng, Qi Wang and Erpeng Wang and has published in prestigious journals such as Chemical Engineering Journal, Frontiers in Psychology and Separation and Purification Technology.

In The Last Decade

Gao Jun

42 papers receiving 356 citations

Hit Papers

Rational design of a novel MIL-100(Fe)/TpPa-1 COF direct ... 2025 2026 2025 10 20 30 40
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.

  1. Rational design of a novel MIL-100(Fe)/TpPa-1 COF direct Z-scheme heterojunction for photo-self-Fenton removal of antibiotics: Performance and ecotoxicity assessment
    2025 44 citations Qiang Li, Man Deng et al. Separation and Purification Technology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gao Jun China 9 125 65 62 62 53 52 361
Savita Verma United States 11 119 1.0× 75 1.2× 34 0.5× 27 0.4× 31 0.6× 41 568
Haoran Wu China 10 55 0.4× 95 1.5× 33 0.5× 49 0.8× 49 0.9× 28 305
Jeffrey Wishart United States 11 303 2.4× 69 1.1× 27 0.4× 22 0.4× 75 1.4× 37 542
Zixuan Zhang China 13 29 0.2× 58 0.9× 22 0.4× 25 0.4× 42 0.8× 57 511
Omar M. Shehata Egypt 11 98 0.8× 145 2.2× 74 1.2× 34 0.5× 7 0.1× 79 444
Hongjia Zhang China 11 136 1.1× 93 1.4× 34 0.5× 22 0.4× 105 2.0× 23 314
Azizan As’arry Malaysia 12 56 0.4× 55 0.8× 12 0.2× 75 1.2× 17 0.3× 77 412
Géza Husi Hungary 10 49 0.4× 71 1.1× 31 0.5× 66 1.1× 9 0.2× 87 351
Roushan Kumar India 14 298 2.4× 97 1.5× 17 0.3× 28 0.5× 26 0.5× 35 528

Countries citing papers authored by Gao Jun

Since Specialization
Citations

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

Fields of papers citing papers by Gao Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gao Jun

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

All Works

20 of 20 papers shown
1.
Li, Qiang, Man Deng, Gao Jun, et al.. (2025). Rational design of a novel MIL-100(Fe)/TpPa-1 COF direct Z-scheme heterojunction for photo-self-Fenton removal of antibiotics: Performance and ecotoxicity assessment. Separation and Purification Technology. 362. 131722–131722. 44 indexed citations breakdown →
2.
Chen, Si-Wei, Gao Jun, Peng Wang, et al.. (2025). In-situ synthesis of SU-102@Ti3C2 Ohmic heterojunction for water purification. Separation and Purification Technology. 378. 134672–134672. 5 indexed citations
3.
4.
Jin, Limin, Man Deng, Gao Jun, et al.. (2025). A crystalline triazine covalent organic framework with partial fluorination for efficient hydrogen peroxide production toward water treatment. Chemical Engineering Journal. 515. 163722–163722. 21 indexed citations
5.
Jun, Gao, Yongqi Li, Ziqiang Cao, & Wenjie Li. (2025). Interleaved-Modal Chain-of-Thought. 19520–19529.
6.
Yuan, Rui, et al.. (2024). A novel rehabilitation action recognition approach using AF-LiteFormer from millimeter wave radar. Measurement Science and Technology. 35(12). 126139–126139. 2 indexed citations
7.
Jun, Gao, et al.. (2024). An efficient driving behavior prediction approach using physiological auxiliary and adaptive LSTM. Machine Vision and Applications. 35(5). 2 indexed citations
8.
Jun, Gao, et al.. (2024). The guardians: Do hometown CEOs curb controlling shareholders' tunneling?. International Review of Financial Analysis. 96. 103602–103602. 1 indexed citations
9.
Jun, Gao, et al.. (2023). Multi-scale space-time transformer for driving behavior detection. Multimedia Tools and Applications. 82(16). 24289–24308. 1 indexed citations
10.
11.
Jun, Gao. (2023). Analysis of the Influence of Financial Informatization on Improving Financial Control Ability. Science and Technology Development Journal. 1 indexed citations
12.
13.
Jun, Gao, et al.. (2022). Attention-based global context network for driving maneuvers prediction. Machine Vision and Applications. 33(4). 8 indexed citations
14.
Chen, Meng, et al.. (2022). Lightweight and Optimization Acceleration Methods for Vision Transformer: A Review. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). 2154–2160. 5 indexed citations
15.
Wei, Yuan, et al.. (2021). How Does House Demolition Affect Family Conspicuous Consumption?. Frontiers in Psychology. 12. 741006–741006. 3 indexed citations
16.
Jun, Gao, et al.. (2020). Control Strategy for Shift Schedule Correction Based on Driving Habits for Vehicles with Automatic Transmission. International Journal of Automotive Technology. 21(2). 407–418. 5 indexed citations
17.
Jun, Gao, et al.. (2018). Multivariate time series prediction of lane changing behavior using deep neural network. Applied Intelligence. 48(10). 3523–3537. 65 indexed citations
18.
Jun, Gao, et al.. (2016). Moving object detection for video surveillance based on improved ViBe. 6259–6263. 9 indexed citations
19.
Jun, Gao. (2012). ELF/SLF/VLF broadband H-filed sensor. Chinese Journal of Radio Science. 1 indexed citations
20.
Jun, Gao, et al.. (2008). Study on the Forecasting and Early Warning Index System for Work Safety. Zhongguo anquan kexue xuebao.

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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