Zhehong Wang

689 total citations
31 papers, 412 citations indexed

About

Zhehong Wang is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhehong Wang has authored 31 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Atomic and Molecular Physics, and Optics, 12 papers in Electrical and Electronic Engineering and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhehong Wang's work include Color Science and Applications (13 papers), Advanced Memory and Neural Computing (8 papers) and Ferroelectric and Negative Capacitance Devices (5 papers). Zhehong Wang is often cited by papers focused on Color Science and Applications (13 papers), Advanced Memory and Neural Computing (8 papers) and Ferroelectric and Negative Capacitance Devices (5 papers). Zhehong Wang collaborates with scholars based in China, United States and Taiwan. Zhehong Wang's co-authors include Haisong Xu, Fuzheng Zhang, Qing Wang, David Blaauw, Yu-Der Chih, Qing Dong, Yi-Chun Shih, Jonathan Chang, Dennis Sylvester and Yiqun Zhang and has published in prestigious journals such as IEEE Journal of Solid-State Circuits, Journal of Physics D Applied Physics and Journal of the Optical Society of America A.

In The Last Decade

Zhehong Wang

29 papers receiving 397 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zhehong Wang China 10 195 151 70 69 62 31 412
Sanchali Das India 10 94 0.5× 119 0.8× 46 0.7× 33 0.5× 33 0.5× 26 400
Nianyu Zou China 16 457 2.3× 200 1.3× 34 0.5× 61 0.9× 26 0.4× 74 650
Kenneth L. Kelly United States 4 21 0.1× 124 0.8× 60 0.9× 20 0.3× 120 1.9× 5 436
A. Vorozcovs Canada 7 78 0.4× 266 1.8× 17 0.2× 18 0.3× 356 5.7× 16 543
Eva M. Valero Spain 13 41 0.2× 317 2.1× 49 0.7× 27 0.4× 210 3.4× 78 582
Laurent Blondé France 8 39 0.2× 125 0.8× 80 1.1× 18 0.3× 94 1.5× 38 304
Matthew Trentacoste Canada 9 77 0.4× 312 2.1× 22 0.3× 21 0.3× 656 10.6× 13 799
Kenjiro Hashimoto Japan 13 37 0.2× 466 3.1× 383 5.5× 44 0.6× 121 2.0× 39 569
Michael Stokes United States 4 25 0.1× 195 1.3× 61 0.9× 8 0.1× 272 4.4× 9 441

Countries citing papers authored by Zhehong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Zhehong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhehong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhehong Wang. A scholar is included among the top collaborators of Zhehong Wang 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 Zhehong Wang. Zhehong Wang 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.
Zhang, Qirui, Zhehong Wang, Ziyun Li, et al.. (2024). RoboVisio: A Micro-Robot Vision Domain-Specific SoC for Autonomous Navigation Enabling Fully-on-Chip Intelligence via 2-MB eMRAM. IEEE Journal of Solid-State Circuits. 59(8). 2644–2658.
2.
Zhang, Qirui, Li Xu, Ang Cao, et al.. (2024). AIMMI: Audio and Image Multi-Modal Intelligence via a Low-Power SoC With 2-MByte On-Chip MRAM for IoT Devices. IEEE Journal of Solid-State Circuits. 59(10). 3488–3501.
3.
Wang, Weizong, et al.. (2024). Deposition characteristics and influence regularity of sputtered products in a low-power RF gridded ion thruster. Vacuum. 228. 113472–113472. 2 indexed citations
4.
Zhang, Qirui, Zhehong Wang, Ziyun Li, et al.. (2022). A 22nm 3.5TOPS/W Flexible Micro-Robotic Vision SoC with 2MB eMRAM for Fully-on-Chip Intelligence. 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits). 72–73. 9 indexed citations
5.
Zhang, Qirui, Li Xu, Ang Cao, et al.. (2022). Audio and Image Cross-Modal Intelligence via a 10TOPS/W 22nm SoC with Back-Propagation and Dynamic Power Gating. 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits). 18–19. 9 indexed citations
6.
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
7.
Li, Ziyun, Zhehong Wang, Li Xu, et al.. (2020). RRAM-DNN: An RRAM and Model-Compression Empowered All-Weights-On-Chip DNN Accelerator. IEEE Journal of Solid-State Circuits. 56(4). 1105–1115. 23 indexed citations
8.
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
9.
Wang, Zhehong, Tianjun Zhang, Daichi Fujiki, et al.. (2020). A 2.46M reads/s Genome Sequencing Accelerator using a 625 Processing-Element Array. 3 indexed citations
10.
Wang, Zhehong, Ziyun Li, Li Xu, et al.. (2020). An All-Weights-on-Chip DNN Accelerator in 22nm ULL Featuring 24×1 Mb eRRAM. 1–2. 5 indexed citations
11.
Dong, Qing, Zhehong Wang, Jongyup Lim, et al.. (2018). A 1-Mb 28-nm 1T1MTJ STT-MRAM With Single-Cap Offset-Cancelled Sense Amplifier and <italic>In Situ</italic> Self-Write-Termination. IEEE Journal of Solid-State Circuits. 54(1). 231–239. 41 indexed citations
12.
Jeloka, Supreet, et al.. (2018). Energy Efficient Adiabatic FRAM with 0.99 PJ/Bit Write for IoT Applications. 85–86. 1 indexed citations
14.
Zhang, Fuzheng, Haisong Xu, & Zhehong Wang. (2017). Optimizing spectral compositions of multichannel LED light sources by IES color fidelity index and luminous efficacy of radiation: publisher’s note. Applied Optics. 56(11). 3022–3022. 1 indexed citations
15.
Zhang, Fuzheng, et al.. (2017). Spectral estimation of tunable LED light source using digital camera based on matrix factorization. Optik. 148. 90–94. 2 indexed citations
16.
Zhang, Fuzheng, Haisong Xu, & Zhehong Wang. (2017). Optimizing spectral compositions of multichannel LED light sources by IES color fidelity index and luminous efficacy of radiation. Applied Optics. 56(7). 1962–1962. 37 indexed citations
17.
Wang, Qing, Haisong Xu, Fuzheng Zhang, & Zhehong Wang. (2016). Influence of color temperature on comfort and preference for LED indoor lighting. Optik. 129. 21–29. 91 indexed citations
18.
Xu, Haisong, et al.. (2016). Spectral estimation of fluorescent lamps using RGB digital camera and standard color chart. Optik. 130. 50–60. 4 indexed citations
19.
Wang, Zhehong & Haisong Xu. (2014). Evaluation of small suprathreshold color differences under different background colors. Chinese Optics Letters. 12(2). 23301–23304. 2 indexed citations
20.
Wang, Zhehong & Haisong Xu. (2008). Investigations of suprathreshold color-difference tolerances with different visual scales and different perceptual correlates using CRT colors. Journal of the Optical Society of America A. 25(12). 2908–2908. 1 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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