Ying Nan

811 citations
60 papers · 599 indexed · h-index 14

Impact in

Papers in

Ying Nan

53 papers receiving 575 citations

Peers

Ying Nan
Comparison fields: 5 of 108
  • Aerospace Engineering 185
  • Biological Psychiatry 13
  • Toxicology 16
  • Computer Vision and Pattern Recognition 92
  • Geriatrics and Gerontology 16
Replace Han Zhang with:
Han Zhang China
Yonghong Gao China
Chen Zhu Australia
Kejian Wu China
Yuping Lin China
Ihsan Ul Haq Pakistan
Yong Seok Heo South Korea
Ang Zhang China
Yanzhu Liu China
Ying Nan relative to Han Zhang China Han Zhang's profile →
Citations per field
00.5×
Han Zhang · 1×
Citations per year

Countries citing papers authored by Ying Nan

Since Specialization
Citations

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

Fields of papers citing papers by Ying Nan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20248
3 20243
4 20241
5 20233
6 20235
7 20231
8 20230
9 20237
10 202220
11 20213
12 202021
13
Effect of Inhibin-βA Subunit Gene on Reproductive Performance of Kazakh Sheep in Non-breeding Season.
20191
14 20175
15 201753
16 201613
17 201423
18 20122
19
Relationship between serum lipids and dietary and non-dietary factors in a Chinese population.
199510
20
The optimal return trajectory design of space vehicle
19934

About Ying Nan

Ying Nan is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition, Sensory Systems, Control and Systems Engineering and Pathology and Forensic Medicine, having authored 60 papers that have together received 599 indexed citations. Recurring topics across this work include Guidance and Control Systems (14 papers), Robotic Path Planning Algorithms (14 papers), Military Defense Systems Analysis (10 papers), Adaptive Control of Nonlinear Systems (6 papers), Spacecraft Dynamics and Control (5 papers), Mycobacterium research and diagnosis (3 papers), Cardiac Ischemia and Reperfusion (3 papers) and Sodium Intake and Health (2 papers). The work is most often cited by research in Aerospace Engineering (185 citations), Biological Psychiatry (13 citations), Toxicology (16 citations), Computer Vision and Pattern Recognition (92 citations) and Geriatrics and Gerontology (16 citations). Ying Nan has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Yuping Lu, Guoqiang Huang, Yi Yang, Haoxiang Chen, Yuhong Yang, Zhihan Li, Xiang Wang, Haichang Wang, Yan Zhao and Haifeng Zhang. Their work appears in journals such as Applied Sciences, Aerospace Science and Technology, Journal of Hypertension, The Aeronautical Journal and Frontiers in Immunology.

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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