Hui Han

732 total citations · 1 hit paper
16 papers, 465 citations indexed

About

Hui Han is a scholar working on Artificial Intelligence, Computational Mechanics and Biomedical Engineering. According to data from OpenAlex, Hui Han has authored 16 papers receiving a total of 465 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computational Mechanics and 4 papers in Biomedical Engineering. Recurrent topics in Hui Han's work include Advanced Graph Neural Networks (4 papers), Thermochemical Biomass Conversion Processes (4 papers) and Combustion and flame dynamics (3 papers). Hui Han is often cited by papers focused on Advanced Graph Neural Networks (4 papers), Thermochemical Biomass Conversion Processes (4 papers) and Combustion and flame dynamics (3 papers). Hui Han collaborates with scholars based in China. Hui Han's co-authors include Chuan Shi, Xiao Wang, Nian Liu, Zhengqi Li, Lingyan Zeng, Zhichao Chen, Qingxiang Wang, Yue Zhao, Chenqiang Gao and Lin Tang and has published in prestigious journals such as Applied Energy, Energy and Sensors.

In The Last Decade

Hui Han

14 papers receiving 460 citations

Hit Papers

Self-supervised Heterogeneous Graph Neural Network with C... 2021 2026 2022 2024 2021 50 100 150 200
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. Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning
    2021 235 citations Xiao Wang, Nian Liu 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
Hui Han China 8 239 113 89 70 64 16 465
Katharina Beckh Germany 4 188 0.8× 29 0.3× 38 0.4× 44 0.6× 21 0.3× 8 493
Bogdan Georgiev Germany 2 186 0.8× 29 0.3× 37 0.4× 46 0.7× 21 0.3× 8 483
Laura von Rueden Germany 3 187 0.8× 28 0.2× 39 0.4× 45 0.6× 21 0.3× 5 485
Lin Yan China 13 62 0.3× 19 0.2× 94 1.1× 54 0.8× 35 0.5× 63 549
Linjun Sun China 14 213 0.9× 94 0.8× 338 3.8× 11 0.2× 53 0.8× 38 651
Hao Hu China 12 164 0.7× 33 0.3× 185 2.1× 28 0.4× 11 0.2× 41 469
Zhaowei Liu China 12 131 0.5× 49 0.4× 90 1.0× 17 0.2× 26 0.4× 43 457
Junlong Zhu China 13 200 0.8× 61 0.5× 45 0.5× 9 0.1× 41 0.6× 80 583
Kejing He China 12 146 0.6× 106 0.9× 32 0.4× 29 0.4× 30 0.5× 46 354

Countries citing papers authored by Hui Han

Since Specialization
Citations

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

Fields of papers citing papers by Hui Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hui Han

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

All Works

16 of 16 papers shown
1.
2.
Yang, Cheng, et al.. (2023). GammaGL: A Multi-Backend Library for Graph Neural Networks. 2861–2870. 2 indexed citations
3.
Liu, Nian, Xiao Wang, Hui Han, & Chuan Shi. (2023). Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering. 35(10). 10884–10896. 7 indexed citations
4.
Han, Hui, et al.. (2022). OpenHGNN: An Open Source Toolkit for Heterogeneous Graph Neural Network. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 3993–3997. 20 indexed citations
5.
Wang, Xiao, Nian Liu, Hui Han, & Chuan Shi. (2021). Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. 1726–1736. 235 indexed citations breakdown →
6.
Li, Xiaoguang, Lingyan Zeng, Hongye Liu, et al.. (2020). Numerical simulation investigations into the influence of the mass ratio of pulverized-coal in fuel-rich flow to that in fuel-lean flow on the combustion and NOx generation characteristics of a 600-MW down-fired boiler. Environmental Science and Pollution Research. 27(14). 16900–16915. 6 indexed citations
7.
8.
Wang, Qingxiang, Zhichao Chen, Hui Han, Lingyan Zeng, & Zhengqi Li. (2019). Experimental characterization of anthracite combustion and NO emission for a 300-MWe down-fired boiler with a novel combustion system: Influence of primary and vent air distributions. Applied Energy. 238. 1551–1562. 49 indexed citations
9.
10.
Li, Xiaoguang, Lingyan Zeng, Hongye Liu, et al.. (2019). Numerical simulation study on the influences of the secondary-tertiary air proportion on the airflow mixing effects and pulverized coal combustion characteristics in a 300-MW down-fired boiler. Process Safety and Environmental Protection. 130. 326–343. 5 indexed citations
11.
Wang, Guoliang, et al.. (2019). Radar Emitter Identification under Transfer Learning and Online Learning. Information. 11(1). 15–15. 10 indexed citations
12.
Han, Hui, et al.. (2018). Polycrystalline silicon wafer defect segmentation based on deep convolutional neural networks. Pattern Recognition Letters. 130. 234–241. 68 indexed citations
13.
14.
Wang, Fan, et al.. (2013). The Complexity Evaluation Method of Electromagnetic Environment Based on Statistical Characteristics Analysis. Applied Mechanics and Materials. 321-324. 779–784.
15.
Xuan, Guixin, et al.. (2012). Removing illumination from image pair for stereo matching. 25. 508–512. 3 indexed citations
16.
Wu, Xiaojuan, et al.. (2006). Research of a Real-time Hand Tracking Algorithm. 2. 1233–1235. 5 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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