Jiahao Song: h-index, Total Citations, and Citation Map
Jiahao Song's h-index is 15 (23 i10-index, 589+ total citations across 42+ publications) according to Google Scholar as of June 2026. Jiahao Song is affiliated with Postdoctoral Scholar, UC San Diego.
Jiahao Song is a researcher affiliated with Postdoctoral Scholar, UC San Diego, specializing in memory design, compute-in-memory, analog computing. Their work has been cited 589 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Jiahao Song's Citation Metrics
Bibliometric impact based on 42 indexed publications.
- H-Index
- 15
- i10-Index
- 23
- Total Citations
- 589
- Citing Countries
- 32
As of June 2026.
Jiahao Song has an h-index of 15 and 589 total citations across 42 publications, with research cited by institutions in 32 countries.
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Global Impact Map
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TD-SRAM: Time-domain-based in-memory computing macro for binary neural networks
202182
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.
160 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered time-domain SRAM-based in-memory computing macros for binary neural networks, establishing a foundational architecture for efficient, sparse, and signed-operand AI hardware acceleration.
The researcher developed a scalable, reconfigurable charge-domain SRAM in-memory computing macro, advancing robust transpose operations and sparsity-optimized multi-mode MAC capabilities for efficient neural network acceleration.
The researcher developed a calibration-free 4-bit computing-in-memory macro using eDRAM, establishing a foundation for efficient, multi-precision edge AI inference and on-device fine-tuning systems.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Jiahao Song's research
Jiahao Song is a researcher in memory design, compute-in-memory and analog computing at Postdoctoral Scholar, UC San Diego. Their work has been cited 589 times across 42 publications (h-index 15), according to Google Scholar.
Their most-cited work, “TD-SRAM: Time-domain-based in-memory computing macro for binary neural networks” (2021), has accumulated 82 citations. Other influential works include “A 28 nm 16 kb bit-scalable charge-domain transpose 6T SRAM in-memory computing macro” (2023) with 42 citations and “A 65 nm 73 kb SRAM-based computing-in-memory macro with dynamic-sparsity controlling” (2022) with 32 citations.
Citations of Jiahao Song's research come primarily from China, United States and South Korea, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
