Jun Pan

1.2k citations
82 papers · 832 · h-index 15

Impact in

Papers in

Jun Pan

75 papers receiving 801 citations

Peers

Jun Pan
Comparison fields: 5 of 143
  • Language and Linguistics 133
  • Rehabilitation 42
  • Energy Engineering and Power Technology 21
  • Sensory Systems 30
  • Horticulture 6
Replace Chris Hopkins with:
Chris Hopkins United States
Ruixin Wang China
Bokai Wang China
Alireza Sadeghpour Iran
Xinran Zhang China
Fei Yu China
Jung‐Chul Park South Korea
JOSEPH C. WOOD United States
Daniel F. Smith United States
Jun Pan relative to Chris Hopkins United States Chris Hopkins's profile →
Citations per field
00.5×5×10×15×19×
Chris Hopkins · 1×
Citations per year

Countries citing papers authored by Jun Pan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020138
2 201950
3 202248
4 201433
5 202331
6 201028
7 201328
8 201826
9 201724
10 201524
11 201822
12 201221
13 201221
14 201421
15 201518
16 201615
17 202415
18 201715
19 202414
20 201513

About Jun Pan

Jun Pan is a scholar working on Language and Linguistics, Energy Engineering and Power Technology, General Health Professions, Artificial Intelligence and Rehabilitation, having authored 82 papers that have together received 832 indexed citations. Recurring topics across this work include Interpreting and Communication in Healthcare (18 papers), Translation Studies and Practices (13 papers), Natural Language Processing Techniques (7 papers), Hybrid Renewable Energy Systems (6 papers), EFL/ESL Teaching and Learning (5 papers), Elbow and Forearm Trauma Treatment (4 papers), Discourse Analysis in Language Studies (4 papers) and Language, Discourse, Communication Strategies (3 papers). The work is most often cited by research in Language and Linguistics (133 citations), Rehabilitation (42 citations), Energy Engineering and Power Technology (21 citations), Sensory Systems (30 citations) and Horticulture (6 citations). Jun Pan has collaborated with scholars based in China, Hong Kong and Japan. Frequent co-authors include Jackie Xiu Yan, Honghua Wang, Xiaobo Zhou, Shan Ou, Quanhua Liu, Li Hua, Guodong Liu, Penghai Wu, Xiaoshuang Ma and Xiangchao Meng. Their work appears in journals such as The Interpreter and Translator Trainer, Perspectives, Journal of Orthopaedic Surgery and Research, Energy Conversion and Management X and Applied Mathematics and Nonlinear Sciences.

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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