Heng Chang

973 citations
39 papers · 409 · h-index 12

Impact in

Papers in

Heng Chang

38 papers receiving 403 citations

Peers

Heng Chang
Comparison fields: 5 of 56
  • Artificial Intelligence 236
  • Industrial and Manufacturing Engineering 66
  • Computer Vision and Pattern Recognition 84
  • Statistical and Nonlinear Physics 41
  • Computational Mechanics 56
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Shuning Wang China
Xiangle Cheng China
Omkar Pathak United States
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Citations per field
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Citations per year

Countries citing papers authored by Heng Chang

Since Specialization
Citations

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

Fields of papers citing papers by Heng Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Heng Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Heng Chang Line = papers co-authored together Heng Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202085
2 198742
3 202224
4 199320
5 202319
6 202319
7 202118
8 202216
9 202315
10
Not All Low-Pass Filters are Robust in Graph Convolutional Networks
202114
11 202113
12 198813
13
The CUHK Dysarthric Speech Recognition Systems for English and Cantonese.
201911
14 202311
15 198711
16 20229
17 19889
18 20238
19 20247
20 20236

About Heng Chang

Heng Chang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanical Engineering, Materials Chemistry and Industrial and Manufacturing Engineering, having authored 39 papers that have together received 409 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (15 papers), Topic Modeling (7 papers), Text and Document Classification Technologies (4 papers), Manufacturing Process and Optimization (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Adversarial Robustness in Machine Learning (3 papers), Complex Network Analysis Techniques (3 papers) and Machine Learning in Materials Science (3 papers). The work is most often cited by research in Artificial Intelligence (236 citations), Industrial and Manufacturing Engineering (66 citations), Computer Vision and Pattern Recognition (84 citations), Statistical and Nonlinear Physics (41 citations) and Computational Mechanics (56 citations). Heng Chang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Wenwu Zhu, Yu Rong, Junzhou Huang, Tingyang Xu, Richard A. Wysk, Wenbing Huang, Jia Li, Honglei Zhang, Peng Cui and Hsu‐Pin Wang. Their work appears in journals such as International Journal of Production Research, IEEE Transactions on Knowledge and Data Engineering, The International Journal of Advanced Manufacturing Technology, Renewable Energy and International Journal of Hydrogen Energy.

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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