Yiran Chen Google Scholar: h-index, Total Citations, and Citation Map
Yiran Chen's h-index is 101 (510 i10-index, 43,429+ total citations across 860+ publications) according to Google Scholar as of October 2026. Yiran Chen is affiliated with John Cocke Distinguished Professor of Electrical and Computer Engineering, Duke University.
Yiran Chen is a researcher affiliated with John Cocke Distinguished Professor of Electrical and Computer Engineering, Duke University, specializing in memory, neuromorphic, machine learning systems. Their work has been cited 43,429 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Yiran Chen's Citation Metrics
Bibliometric impact based on 860 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 101
- i10-Index
- 510
- Total Citations
- 43,429
- Citing Countries
- 60
As of October 2026.
Yiran Chen has an h-index of 101 and 43,429 total citations across 860 publications, with research cited by institutions in 60 countries.
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Global Impact Map
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Learning structured sparsity in deep neural networks
20163,484
Top Citing Countries
Top Citing Institutions
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Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
1510 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered methods for structured sparsity and gradient quantization to enhance deep neural network efficiency, establishing a foundational framework for scalable distributed learning.
The researcher pioneered local distributed mobile computing for deep neural networks, establishing a foundational framework later extended to federated instruction tuning for large language models.
The researcher developed a seminal color image cryptosystem using dynamic DNA encryption and chaos, later extending this framework to integrate compressive sensing for joint compression and encryption.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Yiran Chen's research
Yiran Chen is a researcher in memory, neuromorphic and machine learning systems at John Cocke Distinguished Professor of Electrical and Computer Engineering, Duke University. Their work has been cited 43,429 times across 860 publications (h-index 101), according to Google Scholar.
Their most-cited work, “Learning structured sparsity in deep neural networks” (2016), has accumulated 3,484 citations. Other influential works include “Terngrad: Ternary gradients to reduce communication in distributed deep learning” (2017) with 1,406 citations and “Pipelayer: A pipelined reram-based accelerator for deep learning” (2017) with 1,132 citations.
Citations of Yiran Chen's research come primarily from United States, China and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
