David Blaauw

33.2k total citations · 6 hit papers
684 papers, 24.7k citations indexed

About

David Blaauw is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Biomedical Engineering. According to data from OpenAlex, David Blaauw has authored 684 papers receiving a total of 24.7k indexed citations (citations by other indexed papers that have themselves been cited), including 582 papers in Electrical and Electronic Engineering, 226 papers in Hardware and Architecture and 137 papers in Biomedical Engineering. Recurrent topics in David Blaauw's work include Low-power high-performance VLSI design (327 papers), Advancements in Semiconductor Devices and Circuit Design (116 papers) and VLSI and Analog Circuit Testing (113 papers). David Blaauw is often cited by papers focused on Low-power high-performance VLSI design (327 papers), Advancements in Semiconductor Devices and Circuit Design (116 papers) and VLSI and Analog Circuit Testing (113 papers). David Blaauw collaborates with scholars based in United States, South Korea and United Kingdom. David Blaauw's co-authors include Dennis Sylvester, Trevor Mudge, Krisztián Flautner, Nam Sung Kim, Shidhartha Das, Sanjay Pant, Bo Zhai, Inhee Lee, Vladimir Zolotov and Ronald Dreslinski and has published in prestigious journals such as SHILAP Revista de lepidopterología, Proceedings of the IEEE and Journal of Power Sources.

In The Last Decade

David Blaauw

667 papers receiving 23.8k citations

Hit Papers

Razor: a low-power pipeli... 2002 2026 2010 2018 2003 2004 2010 2002 2009 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
David Blaauw 20.8k 9.9k 4.2k 4.1k 1.3k 684 24.7k
Dennis Sylvester 16.6k 0.8× 5.6k 0.6× 4.4k 1.0× 3.0k 0.7× 774 0.6× 602 19.0k
Kaushik Roy 28.4k 1.4× 8.3k 0.8× 3.8k 0.9× 2.7k 0.7× 3.5k 2.7× 1.0k 32.6k
Jan M. Rabaey 17.1k 0.8× 5.6k 0.6× 6.7k 1.6× 7.6k 1.9× 1.4k 1.1× 438 24.8k
R.W. Brodersen 13.5k 0.7× 4.8k 0.5× 3.6k 0.8× 7.6k 1.9× 793 0.6× 275 19.0k
Andrew B. Kahng 12.6k 0.6× 8.3k 0.8× 1.0k 0.2× 3.7k 0.9× 1.6k 1.3× 611 17.0k
Massoud Pedram 14.0k 0.7× 7.6k 0.8× 1.4k 0.3× 5.0k 1.2× 1.5k 1.2× 887 19.7k
Yu Cao 10.8k 0.5× 2.6k 0.3× 2.3k 0.5× 975 0.2× 1.1k 0.8× 409 13.9k
Anantha P. Chandrakasan 38.2k 1.8× 6.9k 0.7× 12.2k 2.9× 25.2k 6.2× 2.1k 1.6× 575 55.0k
David Z. Pan 9.4k 0.5× 4.4k 0.4× 1.5k 0.4× 1.1k 0.3× 1.4k 1.1× 569 10.9k
Anand Raghunathan 8.4k 0.4× 6.1k 0.6× 1.4k 0.3× 4.5k 1.1× 2.4k 1.8× 400 14.0k

Countries citing papers authored by David Blaauw

Since Specialization
Citations

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

Fields of papers citing papers by David Blaauw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Blaauw

This figure shows the co-authorship network connecting the top 25 collaborators of David Blaauw. A scholar is included among the top collaborators of David Blaauw based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Blaauw. David Blaauw is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lee, Jungho, Li Xu, L. Hanson, et al.. (2025). Microscopic robots that sense, think, act, and compute. Science Robotics. 10(109). eadu8009–eadu8009.
2.
Wang, Yunfan, et al.. (2024). A Low-Power Highly Reconfigurable Analog FIR Filter With 11-Bit Charge-Domain DAC for Narrowband Receivers. IEEE Solid-State Circuits Letters. 7. 74–77. 1 indexed citations
4.
5.
Nason, Samuel R., Jongyup Lim, Matthew S. Willsey, et al.. (2022). A Power-Efficient Brain-Machine Interface System With a Sub-mw Feature Extraction and Decoding ASIC Demonstrated in Nonhuman Primates. IEEE Transactions on Biomedical Circuits and Systems. 16(3). 395–408. 22 indexed citations
6.
Subramaniyan, Arun, Jack Wadden, Xiao Wu, et al.. (2021). Accelerated Seeding for Genome Sequence Alignment with Enumerated Radix Trees. 388–401. 15 indexed citations
7.
Xu, Li, Taekwang Jang, Jongyup Lim, et al.. (2021). A 510-pW 32-kHz Crystal Oscillator With High Energy-to-Noise-Ratio Pulse Injection. IEEE Journal of Solid-State Circuits. 57(2). 434–451. 7 indexed citations
8.
Xu, Li, Kyojin Choo, David Blaauw, & Dennis Sylvester. (2021). An Analog-Assisted Digital LDO With Single Subthreshold Output pMOS Achieving 1.44-fs FOM. IEEE Solid-State Circuits Letters. 4. 154–157. 5 indexed citations
9.
Nason, Samuel R., Alex K. Vaskov, Matthew S. Willsey, et al.. (2020). A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain–machine interfaces. Nature Biomedical Engineering. 4(10). 973–983. 78 indexed citations
10.
Wu, Xiao, Arun Subramaniyan, Zhehong Wang, et al.. (2020). A High-Throughput Pruning-Based Pair-Hidden-Markov-Model Hardware Accelerator for Next-Generation DNA Sequencing. IEEE Solid-State Circuits Letters. 4. 31–35. 7 indexed citations
11.
Wang, Zhehong, Tianjun Zhang, Daichi Fujiki, et al.. (2020). A 2.46M Reads/s Seed-Extension Accelerator for Next-Generation Sequencing Using a String-Independent PE Array. IEEE Journal of Solid-State Circuits. 56(3). 824–833. 1 indexed citations
12.
13.
Choo, Kyojin, Li Xu, Yejoong Kim, et al.. (2019). Energy-Efficient Motion-Triggered IoT CMOS Image Sensor With Capacitor Array-Assisted Charge-Injection SAR ADC. IEEE Journal of Solid-State Circuits. 54(11). 2921–2931. 34 indexed citations
14.
Oh, Sechang, Hun-Seok Kim, Dennis Sylvester, et al.. (2019). An Acoustic Signal Processing Chip With 142-nW Voice Activity Detection Using Mixer-Based Sequential Frequency Scanning and Neural Network Classification. IEEE Journal of Solid-State Circuits. 54(11). 3005–3016. 40 indexed citations
15.
Zhang, Yiqun, Li Xu, Qing Dong, et al.. (2018). Recryptor: A Reconfigurable Cryptographic Cortex-M0 Processor With In-Memory and Near-Memory Computing for IoT Security. IEEE Journal of Solid-State Circuits. 53(4). 995–1005. 88 indexed citations
16.
Dong, Qing, Supreet Jeloka, Mehdi Saligane, et al.. (2017). A 0.3V VDDmin 4+2T SRAM for searching and in-memory computing using 55nm DDC technology. C160–C161. 54 indexed citations
17.
Yang, Kaiyuan, Qing Dong, David Blaauw, & Dennis Sylvester. (2017). 8.3 A 553F2 2-transistor amplifier-based Physically Unclonable Function (PUF) with 1.67% native instability. 146–147. 93 indexed citations
18.
Dong, Qing, Supreet Jeloka, Mehdi Saligane, et al.. (2017). A 4 + 2T SRAM for Searching and In-Memory Computing With 0.3-V $V_{\mathrm {DDmin}}$. IEEE Journal of Solid-State Circuits. 53(4). 1006–1015. 75 indexed citations
19.
Dong, Qing, et al.. (2016). Low-Power and Compact Analog-to-Digital Converter Using Spintronic Racetrack Memory Devices. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 25(3). 907–918. 14 indexed citations
20.
Lin, Yu-Shiang, Dennis Sylvester, & David Blaauw. (2007). A sub-pW timer using gate leakage for ultra low-power sub-Hz monitoring systems. 397–400. 67 indexed citations

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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