Liang Chang

701 total citations
24 papers, 527 citations indexed

About

Liang Chang is a scholar working on Civil and Structural Engineering, Mechanical Engineering and Control and Systems Engineering. According to data from OpenAlex, Liang Chang has authored 24 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Civil and Structural Engineering, 6 papers in Mechanical Engineering and 5 papers in Control and Systems Engineering. Recurrent topics in Liang Chang's work include Infrastructure Resilience and Vulnerability Analysis (6 papers), Advanced Battery Technologies Research (3 papers) and Machine Fault Diagnosis Techniques (3 papers). Liang Chang is often cited by papers focused on Infrastructure Resilience and Vulnerability Analysis (6 papers), Advanced Battery Technologies Research (3 papers) and Machine Fault Diagnosis Techniques (3 papers). Liang Chang collaborates with scholars based in China, United States and Italy. Liang Chang's co-authors include Zhigang Wu, Yan‐Hui Lin, Amr S. Elnashai, Billie F. Spencer, Yi Ren, Zili Wang, Qiang Feng, Cheng Qian, Binghui Xu and Bo Sun and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Physical Chemistry Chemical Physics and Energy.

In The Last Decade

Liang Chang

21 papers receiving 503 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Liang Chang China 10 175 174 131 129 76 24 527
Xiaohong Wang China 14 107 0.6× 107 0.6× 44 0.3× 103 0.8× 89 1.2× 50 526
Zili Wang China 14 303 1.7× 277 1.6× 42 0.3× 75 0.6× 57 0.8× 51 612
Sara Kohtz United States 4 118 0.7× 87 0.5× 51 0.4× 86 0.7× 38 0.5× 11 344
Yue Song China 12 159 0.9× 138 0.8× 33 0.3× 58 0.4× 44 0.6× 35 617
Xiaobang Wang China 14 111 0.6× 109 0.6× 132 1.0× 112 0.9× 17 0.2× 37 520
Lei Sun China 15 317 1.8× 501 2.9× 73 0.6× 58 0.4× 67 0.9× 69 770
Zhaoping Xu China 14 79 0.5× 96 0.6× 52 0.4× 85 0.7× 49 0.6× 57 664
Riti Singh United Kingdom 20 321 1.8× 176 1.0× 25 0.2× 207 1.6× 53 0.7× 81 1.4k
Julie Chalfant United States 13 103 0.6× 98 0.6× 23 0.2× 69 0.5× 29 0.4× 57 455
Estefanía Artigao Spain 11 406 2.3× 225 1.3× 92 0.7× 18 0.1× 100 1.3× 21 594

Countries citing papers authored by Liang Chang

Since Specialization
Citations

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

Fields of papers citing papers by Liang Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liang Chang

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

All Works

20 of 20 papers shown
1.
Chang, Liang & Yan‐Hui Lin. (2025). Few-shot remaining useful life prediction based on Bayesian meta-learning with predictive uncertainty calibration. Engineering Applications of Artificial Intelligence. 142. 109980–109980. 9 indexed citations
2.
Wang, Xinzhe, et al.. (2025). Heat transfer characteristics of R134a vapor flow in a rectangular channel under vibration conditions. Journal of Mechanical Science and Technology. 39(5). 2929–2944.
3.
Yin, Xuan, Chunpeng Chai, Huan Liu, et al.. (2024). Nanostructure of Superlubricating Tribofilm Based on Friction-Induced a-C:H Films under Various Working Conditions: A Review of Solid Lubrication. Lubricants. 12(2). 40–40. 5 indexed citations
4.
Lin, Yan‐Hui, et al.. (2024). Enhanced stochastic recurrent hybrid model for RUL Predictions via Semi-supervised learning. Reliability Engineering & System Safety. 248. 110167–110167. 12 indexed citations
5.
6.
Lin, Yan‐Hui, et al.. (2023). A Semisupervised Deep Hybrid Multitask Model for RUL Prediction. IEEE Transactions on Instrumentation and Measurement. 72. 1–11. 5 indexed citations
7.
Chang, Liang & Yan‐Hui Lin. (2022). Meta-Learning With Adaptive Learning Rates for Few-Shot Fault Diagnosis. IEEE/ASME Transactions on Mechatronics. 27(6). 5948–5958. 47 indexed citations
8.
Yin, Xuan, Haohao Chen, Jiang Lai, et al.. (2022). Effects of polyacrylic acid molecular weights on V2C-MXene nanocoatings for obtaining ultralow friction and ultralow wear in an ambient working environment. Physical Chemistry Chemical Physics. 24(44). 27406–27412. 6 indexed citations
9.
Qian, Cheng, Binghui Xu, Liang Chang, et al.. (2021). Convolutional neural network based capacity estimation using random segments of the charging curves for lithium-ion batteries. Energy. 227. 120333–120333. 135 indexed citations
10.
Lin, Yan‐Hui & Liang Chang. (2021). An Unsupervised Noisy Sample Detection Method for Deep Learning-Based Health Status Prediction. IEEE Transactions on Instrumentation and Measurement. 71. 1–11. 4 indexed citations
11.
Lin, Yan‐Hui & Liang Chang. (2021). An Online Transfer Learning Framework for Time-Varying Distribution Data Prediction. IEEE Transactions on Industrial Electronics. 69(6). 6278–6287. 16 indexed citations
12.
Chang, Liang, Yan‐Hui Lin, & Enrico Zio. (2021). Remaining useful life prediction for complex systems considering varying future operational conditions. Quality and Reliability Engineering International. 38(1). 516–531. 13 indexed citations
13.
Chang, Liang, Amr S. Elnashai, & Billie F. Spencer. (2011). Post-earthquake modelling of transportation networks. Structure and Infrastructure Engineering. 1–19. 58 indexed citations
14.
Zhang, Chao, et al.. (2011). Influence of optical simple pulse coding on the Brillouin optical time domain analyzer based on bi-directional Raman amplification. Acta Physica Sinica. 60(10). 104211–104211. 1 indexed citations
15.
Chang, Liang & Zhigang Wu. (2011). Performance and reliability of electrical power grids under cascading failures. International Journal of Electrical Power & Energy Systems. 33(8). 1410–1419. 110 indexed citations
16.
Zhang, Chao, et al.. (2010). Brillouin optical time domain analyzer based on bi-directional Raman amplification. Acta Physica Sinica. 59(8). 5523–5523. 5 indexed citations
17.
Chang, Liang. (2010). Transportation system modeling and applications in earthquake engineering. Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign). 16 indexed citations
18.
Chang, Liang, Fan Peng, & Yanfeng Ouyang. (2009). Strategic Budget Planning for Seismic Retrofit of Bridge Networks. Transportation Research Board 88th Annual MeetingTransportation Research Board. 1 indexed citations
19.
20.
Chang, Liang & Junho Song. (2007). Matrix-based System Reliability Analysis of Urban Infrastructure Networks: A Case Study of MLGW Natural Gas Network. Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign). 17 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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