Xuchao Ye

438 total citations · 1 hit paper
11 papers, 324 citations indexed

About

Xuchao Ye is a scholar working on Aerospace Engineering, Electrical and Electronic Engineering and Civil and Structural Engineering. According to data from OpenAlex, Xuchao Ye has authored 11 papers receiving a total of 324 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Aerospace Engineering, 7 papers in Electrical and Electronic Engineering and 1 paper in Civil and Structural Engineering. Recurrent topics in Xuchao Ye's work include UAV Applications and Optimization (8 papers), Millimeter-Wave Propagation and Modeling (5 papers) and Advanced MIMO Systems Optimization (2 papers). Xuchao Ye is often cited by papers focused on UAV Applications and Optimization (8 papers), Millimeter-Wave Propagation and Modeling (5 papers) and Advanced MIMO Systems Optimization (2 papers). Xuchao Ye collaborates with scholars based in China, Pakistan and United States. Xuchao Ye's co-authors include Tao Jin, Yang Ding, Qiuming Zhu, Kai Mao, Xuesong Cai, Jorge Gomez‐Ponce, Yang Miao, Cheng‐Xiang Wang, Qihui Wu and Zhuangzhuang Cui and has published in prestigious journals such as IEEE Internet of Things Journal, Applied Soft Computing and IEEE Transactions on Instrumentation and Measurement.

In The Last Decade

Xuchao Ye

7 papers receiving 320 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review on deep learning-based structural health monitoring of civil infrastructures

2019 245 citations Xuchao Ye, Tao Jin et al. Smart Structures and Systems profile →

Peers

Xuchao Ye

CSE

ME

AE

MM

EEE

Yanjie Zhu China

Junhee Kim South Korea

Zhili He China

Deegan Atha United States

Zhanxiong Ma South Korea

Özgür Kurç Türkiye

Gaetano Miraglia Italy

Shi Qiu China

Yanbin Shen China

Loris Vincenzi Italy

Yanjie Zhu China

Xuchao Ye

226 ×1.0

CSE

47 ×0.9

ME

17 ×0.4

AE

43 ×1.0

MM

33 ×0.8

EEE

Citations per year, relative to Xuchao Ye Xuchao Ye (= 1×) peers Yanjie Zhu

Countries citing papers authored by Xuchao Ye

Since Specialization

Citations

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

Fields of papers citing papers by Xuchao Ye

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xuchao Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Xuchao Ye. A scholar is included among the top collaborators of Xuchao Ye 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 Xuchao Ye. Xuchao Ye is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

1.

Liu, Chang, et al.. (2025). Intelligent decision making under conflicting and cooperative scenarios with incomplete information. Applied Soft Computing. 173. 112898–112898.

2.

Ye, Xuchao, et al.. (2024). Cross-Correlation Characteristic Measurements and Analysis for Multi-Link A2G Channels Based on a Multi-UAV System. Drones. 8(8). 416–416.

3.

Mao, Kai, Qiuming Zhu, Cheng‐Xiang Wang, et al.. (2024). A Survey on Channel Sounding Technologies and Measurements for UAV-Assisted Communications. IEEE Transactions on Instrumentation and Measurement. 73. 1–24. 48 indexed citations

4.

Mao, Kai, Qiuming Zhu, Xuchao Ye, et al.. (2024). Demo Abstract: A UAV-Based Real-Time Channel Knowledge Mapping System. 1–2.

5.

Liu, Yuanjian, Kai Mao, Qiuming Zhu, et al.. (2024). Semantic-Based Channel State Information Feedback for AAV-Assisted ISAC Systems. IEEE Internet of Things Journal. 12(5). 4981–4991. 1 indexed citations

6.

Chen, Xiaohong, Kai Mao, Xuchao Ye, et al.. (2024). Channel Knowledge Map Construction Based on a UAV-Assisted Channel Measurement System. Drones. 8(5). 191–191. 4 indexed citations

7.

Mao, Kai, et al.. (2024). Measurement-based Vegetation Penetration Loss Model for UAV-to-Ground Communications. 1–5.

8.

Ye, Xuchao, et al.. (2024). Measurement-Based Channel Characteristics for Air-to-Ground Communications Under Rural Areas. 3 indexed citations

9.

Mao, Kai, Xuchao Ye, Taotao Zhang, et al.. (2023). Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks. Drones. 7(12). 701–701. 5 indexed citations

10.

Ye, Xuchao, et al.. (2019). A review on deep learning-based structural health monitoring of civil infrastructures. Smart Structures and Systems. 24(5). 567–585. 245 indexed citations breakdown →

11.

Ye, Xuchao, et al.. (2019). Machine learning approaches for wind speed forecasting using long-term monitoring data: a comparative study. Smart Structures and Systems. 24(6). 733–744. 18 indexed citations

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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