Jun Wang

45.9k citations
953 papers · 34.5k indexed · 16 hit papers · h-index 100

Jun Wang

890 papers receiving 33.6k citations

Hit Papers

Advances...1851992202620032014100200300400500

Peers

Jun Wang
Comparison fields: 5 of 218
  • Computer Networks and Communications 12.6k
  • Control and Systems Engineering 11.2k
  • Statistical and Nonlinear Physics 4.5k
  • Artificial Intelligence 11.2k
  • Computer Vision and Pattern Recognition 3.6k
Replace Brian D. O. Anderson with:
Brian D. O. Anderson Australia
Lihua Xie Singapore
Zidong Wang China
Qing‐Long Han Australia
Huijun Gao China
Tingwen Huang China
Xinghuo Yu Australia
Min Wu China
Johan A. K. Suykens Belgium
Laurent El Ghaoui United States
Jun Wang relative to Brian D. O. Anderson Australia Brian D. O. Anderson's profile →
Citations per field
00.5×5.8×
Brian D. O. Anderson · 1×
Citations per year

Countries citing papers authored by Jun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20252
3 20251
4 20250
5 20243
6 20242
7 20241
8 202414
9 20246
10 20242
11 20244
12 20248
13 20241
14 20247
15 20240
16 20232
17 20230
18
Limb Salvage and Prevention of Ulcer Recurrence in a Chronic Refractory Diabetic Foot Osteomyelitis
20200
19 199510
20
On the trainability, stability, representability, and realizability of artificial neural networks
19914

About Jun Wang

Jun Wang is a scholar working on Control and Systems Engineering, Computer Networks and Communications and Artificial Intelligence, having authored 953 papers that have together received 34.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (209 papers), Neural Networks Stability and Synchronization (132 papers), Advanced Memory and Neural Computing (79 papers), Adaptive Control of Nonlinear Systems (61 papers), Metaheuristic Optimization Algorithms Research (55 papers), Distributed Control Multi-Agent Systems (54 papers), Robotic Mechanisms and Dynamics (44 papers) and Fault Detection and Control Systems (44 papers). The work is most often cited by research in Computer Networks and Communications (12.6k citations), Control and Systems Engineering (11.2k citations) and Statistical and Nonlinear Physics (4.5k citations). Jun Wang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Zhouhua Peng, Qingshan Liu, Zhigang Zeng, Youshen Xia, Dan Wang, Zheng Yan, Jinde Cao, Qing‐Long Han, Zhenyuan Guo and Yunong Zhang. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) and IEEE Transactions on Industrial Electronics.

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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