Hongjun Wang

3.7k citations
152 papers · 2.4k indexed · 1 hit paper · h-index 27

Impact in

Papers in

Hongjun Wang

132 papers receiving 2.2k citations

Hit Papers

Long sequence time-series forecasting with deep learning: A survey 2023 · 164 citations
164202320262024202550100150

Peers

Hongjun Wang
Comparison fields: 5 of 141
  • Management Science and Operations Research 1000
  • Statistics and Probability 319
  • Computer Vision and Pattern Recognition 569
  • Artificial Intelligence 819
  • Computational Mathematics 15
Replace Chris Cornelis with:
Chris Cornelis Belgium
Thomas A. Runkler Germany
Myong K. Jeong United States
Xinyang Deng China
Sebastián Maldonado Chile
Jesús Alcalá‐Fdez Spain
Pawan Lingras Canada
Naoki Abe Japan
Yu Su China
Hongjun Wang relative to Chris Cornelis Belgium Chris Cornelis's profile →
Citations per field
00.5×3.8×
Chris Cornelis · 1×
Citations per year

Countries citing papers authored by Hongjun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Hongjun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20242
4 20240
5 20240
6 20242
7 202334
8 202310
9 20231
10 20238
11 20231
12 202327
13 202322
14 20231
15 20237
16 202215
17 202211
18 20226
19 202126
20 202110

About Hongjun Wang

Hongjun Wang is a scholar working on Computer Vision and Pattern Recognition, Management Science and Operations Research, Artificial Intelligence, Ecological Modeling and Urban Studies, having authored 152 papers that have together received 2.4k indexed citations. Recurring topics across this work include Face and Expression Recognition (34 papers), Advanced Clustering Algorithms Research (32 papers), Multi-Criteria Decision Making (27 papers), Optimization and Mathematical Programming (13 papers), Text and Document Classification Technologies (12 papers), Complex Network Analysis Techniques (11 papers), Image Retrieval and Classification Techniques (9 papers) and Rough Sets and Fuzzy Logic (8 papers). The work is most often cited by research in Management Science and Operations Research (1000 citations), Statistics and Probability (319 citations), Computer Vision and Pattern Recognition (569 citations), Artificial Intelligence (819 citations) and Computational Mathematics (15 citations). Hongjun Wang has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Guiwu Wei, Tianrui Li, Rui Lin, Xiaofei Zhao, Xiaofei Zhao, Yan Yang, Jie Hu, Chongshou Li, Minbo Ma and Ping Deng. Their work appears in journals such as Knowledge-Based Systems, International Journal of Computational Intelligence Systems, Journal of Intelligent & Fuzzy Systems, Information Sciences and Technological and Economic Development of Economy.

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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