Sheng Chang

3.5k total citations · 1 hit paper
144 papers, 2.5k citations indexed

About

Sheng Chang is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Sheng Chang has authored 144 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Electrical and Electronic Engineering, 32 papers in Materials Chemistry and 27 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Sheng Chang's work include ECG Monitoring and Analysis (27 papers), Advancements in Semiconductor Devices and Circuit Design (26 papers) and Graphene research and applications (21 papers). Sheng Chang is often cited by papers focused on ECG Monitoring and Analysis (27 papers), Advancements in Semiconductor Devices and Circuit Design (26 papers) and Graphene research and applications (21 papers). Sheng Chang collaborates with scholars based in China, United States and Hong Kong. Sheng Chang's co-authors include Martin Vetterli, Qijun Huang, Bin Yu, Jin He, Hao Wang, Wenhan Liu, Yawei Lv, Fei Wang, Hao Wang and Ruihan Hu and has published in prestigious journals such as Advanced Materials, PLoS ONE and Journal of Applied Physics.

In The Last Decade

Sheng Chang

131 papers receiving 2.3k citations

Hit Papers

Spatially adaptive wavelet thresholding with context mode... 2000 2026 2008 2017 2000 200 400 600
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. Spatially adaptive wavelet thresholding with context modeling for image denoising
    2000 646 citations Sheng Chang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sheng Chang China 23 783 566 561 458 388 144 2.5k
Enbang Li Australia 33 282 0.4× 189 0.3× 2.5k 4.4× 75 0.2× 154 0.4× 223 3.8k
Yuejin Zhao China 21 342 0.4× 147 0.3× 885 1.6× 179 0.4× 129 0.3× 265 2.1k
Huafeng Liu China 20 232 0.3× 244 0.4× 322 0.6× 58 0.1× 337 0.9× 157 2.0k
Yixuan Li China 21 865 1.1× 58 0.1× 288 0.5× 313 0.7× 80 0.2× 86 1.8k
Thierry Blu Switzerland 30 2.9k 3.7× 48 0.1× 348 0.6× 1.1k 2.4× 116 0.3× 83 4.7k
Alan V. Sahakian United States 34 139 0.2× 1.8k 3.2× 530 0.9× 31 0.1× 124 0.3× 139 3.6k
Qijun Huang China 22 140 0.2× 528 0.9× 563 1.0× 11 0.0× 266 0.7× 137 1.6k
Vicente Grau United Kingdom 30 943 1.2× 1.0k 1.8× 92 0.2× 108 0.2× 23 0.1× 144 3.5k
Leslie Ying United States 33 555 0.7× 61 0.1× 87 0.2× 114 0.2× 48 0.1× 157 4.1k
Jin He China 22 112 0.1× 541 1.0× 616 1.1× 11 0.0× 265 0.7× 110 1.6k

Countries citing papers authored by Sheng Chang

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng Chang. A scholar is included among the top collaborators of Sheng 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 Sheng Chang. Sheng 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.
Liu, Wenhan, et al.. (2024). Honest-GE: 2-step heuristic optimization and node-level embedding empower spatial-temporal graph model for ECG. Information Sciences. 677. 120941–120941.
2.
Liu, Wenhan, et al.. (2024). An adaptive threshold-based semi-supervised learning method for cardiovascular disease detection. Information Sciences. 677. 120881–120881. 5 indexed citations
3.
Liu, Wenhan, et al.. (2024). Bootstrap each lead’s latent: A novel method for self-supervised learning of multilead electrocardiograms. Computer Methods and Programs in Biomedicine. 257. 108452–108452. 1 indexed citations
4.
Cheng, Ruiqing, Yanrong Wang, Lei Yin, et al.. (2024). Reconfigurable van der Waals Ferroionic Barristor for Multifunctional Nanoelectronics. Advanced Functional Materials. 34(49). 4 indexed citations
5.
Liu, Wenhan, et al.. (2024). Lead-fusion Barlow twins: A fused self-supervised learning method for multi-lead electrocardiograms. Information Fusion. 114. 102698–102698. 1 indexed citations
6.
7.
Zhang, Zhihan, et al.. (2024). A High-Performance Pixel-Level Fully Pipelined Hardware Accelerator for Neural Networks. IEEE Transactions on Neural Networks and Learning Systems. 36(5). 7970–7983. 3 indexed citations
8.
9.
Liu, Wenhan, et al.. (2023). DDDG: A dual bi-directional knowledge distillation method with generative self-supervised pre-training and its hardware implementation on SoC for ECG. Expert Systems with Applications. 244. 122969–122969. 3 indexed citations
10.
Liu, Wenhan, et al.. (2023). A fully-mapped and energy-efficient FPGA accelerator for dual-function AI-based analysis of ECG. Frontiers in Physiology. 14. 1079503–1079503. 9 indexed citations
11.
Chang, Sheng, et al.. (2023). Modulating Electrical Characteristics of ZnO Thin-Film Transistors by Scaling Down Gate Dielectric Thickness. IEEE Transactions on Electron Devices. 71(2). 1089–1096.
12.
Liu, Wenhan, et al.. (2023). Dense lead contrast for self-supervised representation learning of multilead electrocardiograms. Information Sciences. 634. 189–205. 9 indexed citations
13.
Liu, Wenhan, et al.. (2023). Optimized Solutions of Electrocardiogram Lead and Segment Selection for Cardiovascular Disease Diagnostics. Bioengineering. 10(5). 607–607. 2 indexed citations
14.
Zhai, Baoxing, Ruiqing Cheng, Tianxing Wang, et al.. (2023). First-Principles Prediction of Potential Candidate Materials MCu3X4 (M = V,Nb,Ta;X=S,Se,Te) for Neuromorphic Computing. Physical Review Applied. 19(5). 3 indexed citations
15.
Li, Si‐Zhe, Xue Chen, Li Liu, et al.. (2022). Micron channel length ZnO thin film transistors using bilayer electrodes. Journal of Colloid and Interface Science. 622. 769–779. 10 indexed citations
16.
Wang, Liping, et al.. (2021). The influence of afforestation on land surface temperature in China. National Remote Sensing Bulletin. 25(8). 1862–1872. 3 indexed citations
17.
Wang, Fei, Wenhan Liu, Sheng Chang, et al.. (2019). A novel ECG signal compression method using spindle convolutional auto-encoder. Computer Methods and Programs in Biomedicine. 175. 139–150. 48 indexed citations
18.
Luo, Jiang, Jin He, Hao Wang, et al.. (2018). A 28 GHz LNA using defected ground structure for 5G application. Microwave and Optical Technology Letters. 60(5). 1067–1072. 19 indexed citations
19.
Qin, Wenjing, Renhai Feng, R.P. Doerner, et al.. (2018). Nanochannel structures in W enhance radiation tolerance. Acta Materialia. 153. 147–155. 88 indexed citations
20.
Huang, Qijun, et al.. (2017). Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction. Medical & Biological Engineering & Computing. 56(6). 957–966. 15 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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