Dejun Guo

820 citations
31 papers · 632 · h-index 12

Impact in

Papers in

Dejun Guo

29 papers receiving 611 citations

Peers

Dejun Guo
Comparison fields: 5 of 97
  • Control and Systems Engineering 267
  • Computer Vision and Pattern Recognition 242
  • Aerospace Engineering 161
  • Health Informatics 8
  • Computer Networks and Communications 131
Replace Evan Ackerman with:
Evan Ackerman United States
Pramod Abichandani United States
Dan Yang China
João Sequeira Portugal
Huan Tan United States
Gregory K. Tharp United States
Douglas W. Gage United States
Julián Estévez Spain
Wlodek Kulesza Sweden
George F. Fragulis Greece
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Citations per field
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Citations per year

Countries citing papers authored by Dejun Guo

Since Specialization
Citations

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

Fields of papers citing papers by Dejun Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dejun Guo, 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 Dejun Guo Line = papers co-authored together Dejun Guo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020187
2 2016117
3 201588
4 201759
5 202022
6 202020
7 202016
8 202116
9
Emotion regulation and depression of college students.
200115
10 202115
11
Review of Gross’s Research on Emotion Regulation Process and Strategy
200312
12 201811
13 20179
14 20177
15 20176
16 20216
17 20164
18 20174
19
DIVERGENT CONSEQUENCES OF ANTECEDENT- AND RESPONSE- FOCUSED EMOTION REGULATION
20023
20 20023

About Dejun Guo

Dejun Guo is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering, Computer Networks and Communications and Automotive Engineering, having authored 31 papers that have together received 632 indexed citations. Recurring topics across this work include Adaptive Control of Nonlinear Systems (10 papers), Advanced Vision and Imaging (9 papers), Robotics and Sensor-Based Localization (6 papers), Control and Dynamics of Mobile Robots (5 papers), Robotic Path Planning Algorithms (5 papers), Distributed Control Multi-Agent Systems (3 papers), Force Microscopy Techniques and Applications (2 papers) and Piezoelectric Actuators and Control (2 papers). The work is most often cited by research in Control and Systems Engineering (267 citations), Computer Vision and Pattern Recognition (242 citations), Aerospace Engineering (161 citations), Health Informatics (8 citations) and Computer Networks and Communications (131 citations). Dejun Guo has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Kam K. Leang, Hesheng Wang, Weidong Chen, Xinwu Liang, Guoqiang Hu, Huan Tan, Tao Liu, Yang Shen, Houzhu Ding and Adam King. Their work appears in journals such as IEEE Transactions on Control Systems Technology, IEEE Robotics and Automation Letters, Journal of Nonlinear Science, IEEE Transactions on Aerospace and Electronic Systems and The International Journal of Robotics Research.

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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