Jun Guo

2.2k citations
89 papers · 1.5k · h-index 21

Impact in

Papers in

Jun Guo

77 papers receiving 1.5k citations

Peers

Jun Guo
Comparison fields: 5 of 113
  • Industrial and Manufacturing Engineering 432
  • Management Science and Operations Research 193
  • Marketing 84
  • Environmental Engineering 119
  • Artificial Intelligence 261
Replace Peng Wu with:
Peng Wu China
Emel Kızılkaya Aydoğan Türkiye
Amelia Regan United States
Arijit De India
Joe Naoum‐Sawaya Canada
Shunsheng Guo China
Pablo Cortés Spain
Saeed Asadi Bagloee Australia
Alper Murat United States
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Citations per field
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Citations per year

Countries citing papers authored by Jun Guo

Since Specialization
Citations

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

Fields of papers citing papers by Jun Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010171
2 2017113
3 2019109
4 2021102
5 202296
6 201082
7 202066
8 201158
9 201551
10 201438
11 202336
12 202334
13 202231
14 202228
15 202128
16 202327
17 202327
18 201726
19 202425
20 201622

About Jun Guo

Jun Guo is a scholar working on Industrial and Manufacturing Engineering, Artificial Intelligence, Information Systems, Mechanical Engineering and Control and Systems Engineering, having authored 89 papers that have together received 1.5k indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (17 papers), Scheduling and Optimization Algorithms (17 papers), Advanced Manufacturing and Logistics Optimization (14 papers), Assembly Line Balancing Optimization (9 papers), Sustainable Supply Chain Management (7 papers), Water resources management and optimization (6 papers), Energy Load and Power Forecasting (6 papers) and Hydrological Forecasting Using AI (5 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (432 citations), Management Science and Operations Research (193 citations), Marketing (84 citations), Environmental Engineering (119 citations) and Artificial Intelligence (261 citations). Jun Guo has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Baigang Du, Shunsheng Guo, Xiaorong Huang, Yibing Li, Xiaobing Yu, Kaipu Wang, Shuo Huang, Xiaobing Yu, Qiliang Zhou and Xixing Li. Their work appears in journals such as Expert Systems with Applications, Computers & Industrial Engineering, Engineering Applications of Artificial Intelligence, Theory and applications of categories and Applied Soft Computing.

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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