Song Han Google Scholar: h-index, Total Citations, and Citation Map
Song Han's h-index is 94 (278 i10-index, 106,485+ total citations across 251+ publications) according to Google Scholar as of November 2026. Song Han is affiliated with Massachusetts Institute of Technology.
Song Han is a researcher affiliated with Massachusetts Institute of Technology, specializing in AI & Machine Learning. Their work has been cited 106,485 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Song Han's Citation Metrics
Bibliometric impact based on 251 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 94
- i10-Index
- 278
- Total Citations
- 106,485
- Citing Countries
- 69
As of November 2026.
Song Han has an h-index of 94 and 106,485 total citations across 251 publications, with research cited by institutions in 69 countries.
Global Impact Map
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Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
201513,563
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Song Han's research
Song Han is a researcher in AI & Machine Learning at Massachusetts Institute of Technology. Their work has been cited 106,485 times across 251 publications (h-index 94), according to Google Scholar.
Their most-cited work, “Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding” (2015), has accumulated 13,563 citations. Other influential works include “SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5MB model size” (2016) with 13,006 citations and “Learning both Weights and Connections for Efficient Neural Network” (2015) with 11,239 citations.
Citations of Song Han's research come primarily from China, United States 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.
