Chao-Han Huck Yang

1.4k citations
59 papers · 681 indexed · h-index 14

Chao-Han Huck Yang

54 papers receiving 657 citations

Peers

Chao-Han Huck Yang
Comparison fields: 5 of 77
  • Computational Mathematics 11
  • Signal Processing 177
  • Artificial Intelligence 432
  • Computer Vision and Pattern Recognition 148
  • Health Informatics 5
Replace Syed Zubair with:
Syed Zubair Pakistan
Vidit Jain United States
Shengfeng Pan China
Yuke Wang United States
Chaoqun Hong China
Paul N. Whatmough United States
Sanghoon Kang South Korea
Grigorios G. Chrysos United Kingdom
Thomas Arildsen Denmark
Chao-Han Huck Yang relative to Syed Zubair Pakistan Syed Zubair's profile →
Citations per field
00.5×10×14.1×
Syed Zubair · 1×
Citations per year

Countries citing papers authored by Chao-Han Huck Yang

Since Specialization
Citations

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

Fields of papers citing papers by Chao-Han Huck Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chao-Han Huck Yang. 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 Chao-Han Huck Yang. The network helps show where Chao-Han Huck Yang may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Chao-Han Huck Yang, 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 Chao-Han Huck Yang Line = papers co-authored together Chao-Han Huck Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20251
3 20240
4 20241
5 20247
6 20240
7 202416
8 20240
9 20231
10 202310
11 20233
12 202339
13 202321
14 20222
15 202244
16 20223
17 202110
18 202011
19
When Causal Intervention Meets Image Masking and Adversarial Perturbation for Deep Neural Networks
20192
20
On the Application of Bayesian Analysis and Advanced Signal Processing Techniques for the Impact Monitoring of Smart Structures
20112

About Chao-Han Huck Yang

Chao-Han Huck Yang is a scholar working on Computational Mathematics, Signal Processing and Artificial Intelligence, having authored 59 papers that have together received 681 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (20 papers), Speech and Audio Processing (17 papers), Music and Audio Processing (11 papers), Adversarial Robustness in Machine Learning (8 papers), Quantum Computing Algorithms and Architecture (7 papers), Natural Language Processing Techniques (7 papers), Multimodal Machine Learning Applications (5 papers) and Privacy-Preserving Technologies in Data (5 papers). The work is most often cited by research in Computational Mathematics (11 citations), Signal Processing (177 citations) and Artificial Intelligence (432 citations). Chao-Han Huck Yang has collaborated with scholars based in United States, Italy and China. Frequent co-authors include Pin‐Yu Chen, Jun Qi, Sabato Marco Siniscalchi, Chin‐Hui Lee, Samuel Yen-Chi Chen, Xiaoli Ma, Hao-Hsiang Yang, Yichang Tsai, Yu Tsao and Min-Hsiu Hsieh. Their work appears in journals such as IEEE Transactions on Circuits & Systems II Express Briefs, npj Quantum Information, Structural Health Monitoring, IEEE/ACM Transactions on Audio Speech and Language Processing and Physica Scripta.

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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