Hai‐Kun Wang

810 total citations · 1 hit paper
32 papers, 637 citations indexed

About

Hai‐Kun Wang is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Hai‐Kun Wang has authored 32 papers receiving a total of 637 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Electrical and Electronic Engineering, 7 papers in Computer Vision and Pattern Recognition and 7 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Hai‐Kun Wang's work include Reliability and Maintenance Optimization (6 papers), Energy Load and Power Forecasting (5 papers) and Advanced Battery Technologies Research (4 papers). Hai‐Kun Wang is often cited by papers focused on Reliability and Maintenance Optimization (6 papers), Energy Load and Power Forecasting (5 papers) and Advanced Battery Technologies Research (4 papers). Hai‐Kun Wang collaborates with scholars based in China, United States and Switzerland. Hai‐Kun Wang's co-authors include Yitao Liu, J.-C. Peng, Ke Song, Yi Cheng, Cheng Yi, Yan‐Feng Li, Feng Ma, Hong‐Zhong Huang, Jingdong Chen and Yu Liu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Scientific Reports and Applied Energy.

In The Last Decade

Hai‐Kun Wang

27 papers receiving 612 citations

Hit Papers

Deep belief network based... 2016 2026 2019 2022 2016 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. Deep belief network based deterministic and probabilistic wind speed forecasting approach
    2016 430 citations Hai‐Kun Wang, J.-C. Peng et al. Applied Energy profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hai‐Kun Wang China 8 376 222 90 83 75 32 637
Adnan Saeed China 7 389 1.0× 144 0.6× 67 0.7× 52 0.6× 46 0.6× 17 550
Ahmet Şakir Dokuz Türkiye 12 350 0.9× 250 1.1× 85 0.9× 110 1.3× 41 0.5× 31 729
Kishore Kulat India 15 398 1.1× 119 0.5× 58 0.6× 142 1.7× 69 0.9× 85 836
J.-C. Peng China 6 435 1.2× 151 0.7× 50 0.6× 67 0.8× 66 0.9× 8 561
Zhiyuan Zhao China 11 257 0.7× 165 0.7× 70 0.8× 110 1.3× 62 0.8× 46 548
Mao Yang China 15 609 1.6× 264 1.2× 94 1.0× 107 1.3× 40 0.5× 60 784
Zhewen Niu China 6 351 0.9× 168 0.8× 46 0.5× 41 0.5× 84 1.1× 15 492
Binsu C. Kovoor India 9 258 0.7× 177 0.8× 54 0.6× 53 0.6× 56 0.7× 37 535
Gangqiang Li China 12 900 2.4× 521 2.3× 113 1.3× 100 1.2× 123 1.6× 34 1.2k
Jian Zheng China 13 243 0.6× 95 0.4× 110 1.2× 54 0.7× 69 0.9× 57 704

Countries citing papers authored by Hai‐Kun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Hai‐Kun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai‐Kun Wang. 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 Hai‐Kun Wang. The network helps show where Hai‐Kun Wang may publish in the future.

Co-authorship network of co-authors of Hai‐Kun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Hai‐Kun Wang. A scholar is included among the top collaborators of Hai‐Kun Wang 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 Hai‐Kun Wang. Hai‐Kun Wang 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
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Wang, Hai‐Kun, et al.. (2025). A multi-frequency feature extraction and sparse attention mechanism integrated Mamba model for lithium-ion battery state of health estimation. Journal of Energy Storage. 123. 116643–116643. 4 indexed citations
3.
Su, Zhilong, et al.. (2025). Automatic crack tracking with consistent stereo imaging and wavelet analysis. International Journal of Mechanical Sciences. 304. 110662–110662. 1 indexed citations
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Cui, Hao, et al.. (2025). Characterization of fibre kinking behaviour in thin plate composites at different loading rates. Composites Science and Technology. 270. 111319–111319.
6.
Wang, Hai‐Kun, et al.. (2024). A pyramidal residual attention model of short‐term wind power forecasting for wind farm safety. Quality and Reliability Engineering International. 40(6). 3001–3017. 1 indexed citations
7.
Li, Zhuo, et al.. (2024). Interpreting chemisorption strength with AutoML-based feature deletion experiments. Proceedings of the National Academy of Sciences. 121(12). e2320232121–e2320232121. 6 indexed citations
8.
Wang, Hai‐Kun, et al.. (2024). Experimental and numerical investigation on cavitation collapse reloading and bubble evolution for close-in and contact underwater explosion. Ocean Engineering. 293. 116549–116549. 7 indexed citations
9.
Wang, Hai‐Kun, et al.. (2024). Sparse Transformer-based bins and Polarized Cross Attention decoder for monocular depth estimation. Engineering Science and Technology an International Journal. 54. 101705–101705. 1 indexed citations
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Wang, Hai‐Kun, et al.. (2023). GCNInformer: A combined deep learning model based on GCN and Informer for wind power forecasting. Energy Science & Engineering. 11(10). 3836–3854. 4 indexed citations
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Wang, Hai‐Kun, et al.. (2023). Multi-View 3D Human Pose and Shape Estimation with Epipolar Geometry and Mix-Graphormer. 28–32. 1 indexed citations
14.
Wang, Hai‐Kun, et al.. (2022). A conditional random field based feature learning framework for battery capacity prediction. Scientific Reports. 12(1). 13221–13221. 6 indexed citations
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Du, Jun, Lei Sun, Feng Ma, et al.. (2018). The USTC-iFlytek systems for CHiME-5 Challenge. 11–15. 14 indexed citations
17.
Wang, Hai‐Kun, et al.. (2016). Deep belief network based deterministic and probabilistic wind speed forecasting approach. Applied Energy. 182. 80–93. 430 indexed citations breakdown →
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Wang, Hai‐Kun, Robert Haynes, Hong‐Zhong Huang, Leiting Dong, & Satya N. Atluri. (2015). The Use of High-Performance Fatigue Mechanics and theExtended Kalman / Particle Filters, for Diagnostics andPrognostics of Aircraft Structures. Computer Modeling in Engineering & Sciences. 105(1). 1–24. 9 indexed citations
20.
Wang, Zhiguo, et al.. (2010). Phonetic clustering based confidence measure for embedded speech recognition. 186–189. 2 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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