Jun Geng

34 papers receiving 478 citations

Peers

Jun Geng
Comparison fields: 5 of 73
  • Statistics, Probability and Uncertainty 57
  • Renewable Energy, Sustainability and the Environment 114
  • Statistics and Probability 40
  • Materials Chemistry 189
  • Electronic, Optical and Magnetic Materials 63
Replace Yazhen Wang with:
Yazhen Wang China
Xiaoling Ye China
Haiqing Li China
Kewang Zhang China
W. Herrmann Germany
M. Ross Kunz United States
Dipankar N. Basu India
Lei Yu China
J.-L. Wojkiewicz France
Jun Geng relative to Yazhen Wang China Yazhen Wang's profile →
Citations per field
00.5×4.5×
Yazhen Wang · 1×
Citations per year

Countries citing papers authored by Jun Geng

Since Specialization
Citations

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

Fields of papers citing papers by Jun Geng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Geng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Geng Line = papers co-authored together Jun Geng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005186
2 200734
3 201533
4 201231
5 201327
6 202224
7 202216
8 202316
9 201414
10 201712
11 202312
12 201312
13 20198
14 20167
15 20166
16 20155
17 20185
18 20164
19 20234
20 20203

About Jun Geng

Jun Geng is a scholar working on Statistics, Probability and Uncertainty, Aerospace Engineering, Computer Networks and Communications, Signal Processing and Electrical and Electronic Engineering, having authored 42 papers that have together received 486 indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (11 papers), Radar Systems and Signal Processing (6 papers), Distributed Sensor Networks and Detection Algorithms (6 papers), Direction-of-Arrival Estimation Techniques (6 papers), Statistical Methods and Inference (5 papers), Healthcare Operations and Scheduling Optimization (5 papers), Advanced Statistical Methods and Models (3 papers) and Advanced Algebra and Logic (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (57 citations), Renewable Energy, Sustainability and the Environment (114 citations), Statistics and Probability (40 citations), Materials Chemistry (189 citations) and Electronic, Optical and Magnetic Materials (63 citations). Jun Geng has collaborated with scholars based in China and United States. Frequent co-authors include Lifeng Lai, Hong‐Yuan Chen, Wenhua Hou, Jun‐Jie Zhu, Bingwen Zhang, Liping Jiang, Junhao Xie, Weiyu Xu, Haoran Li and Erhan Bayraktar. Their work appears in journals such as IEEE Transactions on Signal Processing, Digital Signal Processing, Fuzzy Sets and Systems, IET Radar Sonar & Navigation and Journal of Applied Polymer Science.

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.

Explore authors with similar magnitude of impact