Shanshan Ji

809 citations
20 papers · 640 indexed · 2 hit papers · h-index 10
Topics
Machine Fault Diagnosis Techniques (13 papers)Gear and Bearing Dynamics Analysis (10 papers)Synthetic Aperture Radar (SAR) Applications and Techniques (6 papers)
Partner nations
ChinaSingapore

In The Last Decade

Shanshan Ji

18 papers receiving 611 citations

Hit Papers

Batch-normalized deep neural networks for achieving fast ...20182026202020232018202350100150200

Peers

Shanshan Ji
Comparison fields: 5 of 69
  • Control and Systems Engineering 469
  • Mechanical Engineering 292
  • Mechanics of Materials 146
  • Artificial Intelligence 87
  • Electrical and Electronic Engineering 53
Replace Dhiraj Neupane with:
Dhiraj Neupane South Korea
W. Głowacz Poland
Rafia Nishat Toma South Korea
Chenyu Liu China
Thomas W. Rauber Brazil
Jongwon Seok South Korea
Qinghua Zhang China
Xingkai Yang Canada
Shanshan Ji relative to Dhiraj Neupane South Korea Dhiraj Neupane's profile →
Citations per field
00.5×9.8×
Dhiraj Neupane · 1×
Citations per year

Countries citing papers authored by Shanshan Ji

Since Specialization
Citations

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

Fields of papers citing papers by Shanshan Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanshan Ji

This figure shows the co-authorship network connecting the top 25 collaborators of Shanshan Ji. A scholar is included among the top collaborators of Shanshan Ji based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shanshan Ji. Shanshan Ji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 6
3 6
4
Digital twin aided adversarial transfer learning method for domain adaptation fault diagnosisbreakdown →
110
5 8
6 1
7 8
8 17
9 5
10 31
11 36
12 3
13 0
14 22
15 13
16 70
17 14
18 1
19 70
20
Batch-normalized deep neural networks for achieving fast intelligent fault diagnosis of machinesbreakdown →
219

About Shanshan Ji

Shanshan Ji is a scholar working on Control and Systems Engineering, Mechanical Engineering and Aerospace Engineering, having authored 20 papers that have together received 640 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (13 papers), Gear and Bearing Dynamics Analysis (10 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (6 papers). The work is most often cited by research in Control and Systems Engineering (469 citations), Mechanical Engineering (292 citations) and Mechanics of Materials (146 citations). Shanshan Ji has collaborated with scholars based in China and Singapore. Frequent co-authors include Jinrui Wang, Baokun Han, Xingxing Jiang, Huaiqian Bao, Zenghui An, Shunming Li, Weiwei Qian, Zongzhen Zhang, Zhiliang Liu and Haiyan Jin. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Remote Sensing.

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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