Tianchen Liang

1.3k total citations · 2 hit papers
17 papers, 1.0k citations indexed

About

Tianchen Liang is a scholar working on Global and Planetary Change, Control and Systems Engineering and Atmospheric Science. According to data from OpenAlex, Tianchen Liang has authored 17 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Global and Planetary Change, 6 papers in Control and Systems Engineering and 6 papers in Atmospheric Science. Recurrent topics in Tianchen Liang's work include Gear and Bearing Dynamics Analysis (5 papers), Machine Fault Diagnosis Techniques (5 papers) and Atmospheric aerosols and clouds (4 papers). Tianchen Liang is often cited by papers focused on Gear and Bearing Dynamics Analysis (5 papers), Machine Fault Diagnosis Techniques (5 papers) and Atmospheric aerosols and clouds (4 papers). Tianchen Liang collaborates with scholars based in China, Denmark and Switzerland. Tianchen Liang's co-authors include Haidong Shao, Hongkai Jiang, Haizhou Zhang, Shuaipeng Wu, Wenjing Duan, Xingqiu Li, Shunlin Liang, Tao He, Bing Li and Ruishan Zhang and has published in prestigious journals such as Remote Sensing of Environment, IEEE Transactions on Industrial Electronics and Remote Sensing.

In The Last Decade

Tianchen Liang

16 papers receiving 1.0k citations

Hit Papers

Electric Locomotive Bearing Fault Diagnosis Using a Novel... 2017 2026 2020 2023 2017 2017 100 200 300 400
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.

  1. Electric Locomotive Bearing Fault Diagnosis Using a Novel Convolutional Deep Belief Network
    2017 420 citations Haidong Shao, Hongkai Jiang et al. IEEE Transactions on Industrial Electronics profile →
  2. Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing
    2017 326 citations Haidong Shao, Hongkai Jiang et al. Mechanical Systems and Signal Processing profile →

Peers

Tianchen Liang
Carlos Quiterio Gómez Muñoz Spain
Amrit Shankar Verma Norway
Amir R. Nejad Norway
Xiaofeng Liu China
Xin Wu China
Changfu Liu China
Intan Zaurah Mat Darus Malaysia
Liping Sun China
Carlos Quiterio Gómez Muñoz Spain
Tianchen Liang
Citations per year, relative to Tianchen Liang Tianchen Liang (= 1×) peers Carlos Quiterio Gómez Muñoz

Countries citing papers authored by Tianchen Liang

Since Specialization
Citations

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

Fields of papers citing papers by Tianchen Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tianchen Liang

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

All Works

17 of 17 papers shown
1.
Tian, Feng, et al.. (2025). Topographic effects on vegetation greening and area expansion in global alpine zones under climate change. International Journal of Applied Earth Observation and Geoinformation. 142. 104727–104727. 1 indexed citations
2.
Liang, Tianchen, Hongxiao Jin, Torbern Tagesson, et al.. (2024). Global assessment of vegetation patterns along topographic gradients. International Journal of Digital Earth. 17(1). 6 indexed citations
3.
Wang, Jianyu, et al.. (2023). GLRT‐based compressive subspace detectors in single‐frequency multistatic passive radar systems. IET Radar Sonar & Navigation. 18(4). 577–585.
4.
Liang, Tianchen, Shunlin Liang, Lin Sun, et al.. (2022). Estimation of Aerosol Optical Depth at 30 m Resolution Using Landsat Imagery and Machine Learning. Remote Sensing. 14(5). 1053–1053. 12 indexed citations
5.
Zou, Linqing, Feng Tian, Tianchen Liang, et al.. (2022). Assessing the upper elevational limits of vegetation growth in global high-mountains. Remote Sensing of Environment. 286. 113423–113423. 24 indexed citations
6.
Li, Bing, Shunlin Liang, Han Ma, et al.. (2021). Estimation of all-sky 1 km land surface temperature over the conterminous United States. Remote Sensing of Environment. 266. 112707–112707. 44 indexed citations
7.
Liang, Tianchen, et al.. (2021). Retrieval of Regional Aerosol Optical Depth Using Deep Learning. Acta Optica Sinica. 41(4). 401002–401002. 2 indexed citations
8.
Liang, Tianchen, Lin Sun, & Haoxin Li. (2020). MODIS aerosol optical depth retrieval based on random forest approach. Remote Sensing Letters. 12(2). 179–189. 12 indexed citations
9.
Liang, Tianchen, et al.. (2020). Architecture Design of Intelligent Diagnosis System for Airborne Electronic Products Based on Big Data. 15. 116–121. 1 indexed citations
10.
Liang, Tianchen, et al.. (2020). CDAG-Improved Algorithm and Its Application to GF-6 WFV Data Cloud Detection. Acta Optica Sinica. 40(16). 1628001–1628001. 3 indexed citations
11.
Liang, Tianchen, et al.. (2020). GF-6 WFV Data Cloud Detection Based on Improved LCCD Algorithm. Acta Optica Sinica. 40(21). 2128001–2128001. 2 indexed citations
12.
Liang, Tianchen & Lin Sun. (2020). Retrieval of Aerosol Optical Depth (AOD) from the Landsat8 Oli Observations Over Beijing. 8. 5493–5496. 1 indexed citations
13.
Liang, Tianchen, et al.. (2018). Rolling Bearing Fault Diagnosis Using Enhanced Convolutional Neural Network with Compressed Sensing. 148–152. 5 indexed citations
14.
Liang, Tianchen, Shuaipeng Wu, Wenjing Duan, & Ruishan Zhang. (2018). Bearing fault diagnosis based on improved ensemble learning and deep belief network. Journal of Physics Conference Series. 1074. 12154–12154. 28 indexed citations
15.
Shao, Haidong, Hongkai Jiang, Xingqiu Li, & Tianchen Liang. (2018). Rolling bearing fault detection using continuous deep belief network with locally linear embedding. Computers in Industry. 96. 27–39. 158 indexed citations
16.
Shao, Haidong, Hongkai Jiang, Haizhou Zhang, & Tianchen Liang. (2017). Electric Locomotive Bearing Fault Diagnosis Using a Novel Convolutional Deep Belief Network. IEEE Transactions on Industrial Electronics. 65(3). 2727–2736. 420 indexed citations breakdown →
17.
Shao, Haidong, Hongkai Jiang, Haizhou Zhang, et al.. (2017). Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing. Mechanical Systems and Signal Processing. 100. 743–765. 326 indexed citations breakdown →

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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