Ning Ding

271 papers receiving 3.1k citations

Ning Ding's Hit Papers

GAN-based anomaly detection: A review 2022 · 270 citations
2700+1+2Years since publication50100150200250

Peers

Ning Ding
Comparison fields: 5 of 176
  • Ocean Engineering 516
  • Safety, Risk, Reliability and Quality 292
  • Control and Systems Engineering 671
  • Transportation 168
  • Artificial Intelligence 568
Replace Peng Wang with:
Peng Wang China
Yi Liu China
Xiaosheng Si China
Homayoun Najjaran Canada
Xiaogang Jin China
Ting Zhang China
Lefteri H. Tsoukalas United States
Ronghui Zhang China
Ning Ding relative to Peng Wang China Peng Wang's profile →
Citations per field
00.5×1.5×2×2.4×
Peng Wang · 1×
Citations per year

Countries citing papers authored by Ning Ding

Since Specialization
Citations

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

Fields of papers citing papers by Ning Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 297 papers — load more, or switch the sort, to bring in the rest.

#Work
1
GAN-based anomaly detection: A review
Hit paper breakdown →
2022270
2 2020147
3 2021104
4 202197
5 202094
6 202073
7 201868
8 202053
9 201950
10 202049
11 202347
12 202146
13 202143
14 202242
15 202341
16 202041
17 202241
18 202039
19 201838
20 201237

About Ning Ding

Ning Ding is a scholar working on Mechanical Engineering, Artificial Intelligence, Biomedical Engineering, Control and Systems Engineering and Electrical and Electronic Engineering, having authored 297 papers that have together received 3.3k indexed citations. Recurring topics across this work include Evacuation and Crowd Dynamics (31 papers), Cryptography and Data Security (25 papers), Soft Robotics and Applications (17 papers), Advanced machining processes and optimization (14 papers), Complexity and Algorithms in Graphs (13 papers), Laser-Plasma Interactions and Diagnostics (13 papers), Traffic and Road Safety (11 papers) and Robot Manipulation and Learning (11 papers). The work is most often cited by research in Ocean Engineering (516 citations), Safety, Risk, Reliability and Quality (292 citations), Control and Systems Engineering (671 citations), Transportation (168 citations) and Artificial Intelligence (568 citations). Ning Ding has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Tao Chen, Zhiqiang Geng, Yongming Han, Aidong Zhang, Xuan Xia, Xizhou Pan, Nan Li, Lin Ma, Xing He and Xiao Yu. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Measurement, Solar Energy, Water Environment Research and The Science of The Total Environment.

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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