Ting Cui

651 citations
38 papers · 527 · h-index 11

Impact in

Papers in

Ting Cui

34 papers receiving 513 citations

Peers

Ting Cui
Comparison fields: 5 of 88
  • Pharmaceutical Science 33
  • Nutrition and Dietetics 72
  • Agronomy and Crop Science 47
  • Biomaterials 61
  • Rehabilitation 27
Replace Changyun Liu with:
Changyun Liu China
Aida Kistaubayeva Kazakhstan
Sunil Kumar Meena India
Junfang Xia China
N. Rajesh India
MAK Azad Bangladesh
Rajendran Mala India
Mohit Sharma India
Deepti Salvi United States
Shanmugam Sureshkumar South Korea
Ting Cui relative to Changyun Liu China Changyun Liu's profile →
Citations per field
00.5×2×4×6.8×
Changyun Liu · 1×
Citations per year

Countries citing papers authored by Ting Cui

Since Specialization
Citations

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

Fields of papers citing papers by Ting Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016101
2 201571
3 202369
4 201461
5 201738
6 201726
7 201524
8 201816
9 201415
10 201914
11 202312
12
Cotton moisture stress diagnosis based on canopy temperature characteristics calculated from UAV thermal infrared image.
20189
13 20247
14 20157
15 20176
16 20185
17 20195
18 20145
19 20204
20 20254

About Ting Cui

Ting Cui is a scholar working on Energy Engineering and Power Technology, Electrical and Electronic Engineering, Control and Systems Engineering, Biomedical Engineering and Pharmaceutical Science, having authored 38 papers that have together received 527 indexed citations. Recurring topics across this work include Power System Optimization and Stability (7 papers), Microgrid Control and Optimization (7 papers), Power Systems and Renewable Energy (6 papers), HVDC Systems and Fault Protection (5 papers), Biofuel production and bioconversion (4 papers), Wind Turbine Control Systems (4 papers), Power Systems and Technologies (4 papers) and Smart Grid and Power Systems (3 papers). The work is most often cited by research in Pharmaceutical Science (33 citations), Nutrition and Dietetics (72 citations), Agronomy and Crop Science (47 citations), Biomaterials (61 citations) and Rehabilitation (27 citations). Ting Cui has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Qinlu Lin, Huaxi Xiao, Yue Wu, Yan‐Lei Du, Tao Wang, Feng‐Min Li, Jin He, Neil C. Turner, Shizhong Li and Yi Jin. Their work appears in journals such as Energies, Chemical Engineering Journal, Communications Materials, Field Crops Research and Agricultural Water Management.

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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