Shihui Yin

71 total papers · 2.3k total citations
53 papers, 1.6k citations indexed

About

Shihui Yin is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shihui Yin has authored 53 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Electrical and Electronic Engineering, 14 papers in Artificial Intelligence and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shihui Yin's work include Advanced Memory and Neural Computing (30 papers), Ferroelectric and Negative Capacitance Devices (27 papers) and Advanced Neural Network Applications (10 papers). Shihui Yin is often cited by papers focused on Advanced Memory and Neural Computing (30 papers), Ferroelectric and Negative Capacitance Devices (27 papers) and Advanced Neural Network Applications (10 papers). Shihui Yin collaborates with scholars based in United States, China and South Korea. Shihui Yin's co-authors include Jae-sun Seo, Mingoo Seok, Zhewei Jiang, Shimeng Yu, Xiaoyu Sun, Deepak Kadetotad, Xiaochen Peng, Rui Liu, Sang Joon Kim and Minkyu Kim and has published in prestigious journals such as Chemical Engineering Journal, IEEE Journal of Solid-State Circuits and IEEE Transactions on Electron Devices.

In The Last Decade

Shihui Yin

53 papers receiving 1.5k citations

Hit Papers

XNOR-SRAM: In-Memory Comp... 2020 2026 2022 2024 2020 50 100 150 200 250

Author Peers

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

Author Last Decade Papers Cites
Shihui Yin 1.4k 379 231 203 169 53 1.6k
Dongjoo Shin 906 0.7× 341 0.9× 642 2.8× 166 0.8× 57 0.3× 64 1.4k
Tony Tae-Hyoung Kim 1.4k 1.1× 180 0.5× 67 0.3× 367 1.8× 111 0.7× 153 1.7k
G. Jiménez 925 0.7× 177 0.5× 121 0.5× 79 0.4× 481 2.8× 90 1.3k
Minhao Yang 970 0.7× 300 0.8× 249 1.1× 56 0.3× 227 1.3× 41 1.4k
Xing Hu 845 0.6× 613 1.6× 324 1.4× 272 1.3× 108 0.6× 62 1.4k
Anup Das 1.3k 1.0× 247 0.7× 107 0.5× 719 3.5× 204 1.2× 116 1.9k
Jason K. Eshraghian 1.2k 0.9× 366 1.0× 64 0.3× 56 0.3× 473 2.8× 94 1.6k
Abhronil Sengupta 1.7k 1.3× 733 1.9× 163 0.7× 56 0.3× 294 1.7× 79 2.2k
Priyanka Raina 1.3k 1.0× 389 1.0× 451 2.0× 394 1.9× 196 1.2× 64 1.8k
C. Diorio 1.3k 1.0× 368 1.0× 119 0.5× 77 0.4× 371 2.2× 63 1.9k

Countries citing papers authored by Shihui Yin

Since Specialization
Citations

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

Fields of papers citing papers by Shihui Yin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shihui Yin

This figure shows the co-authorship network connecting the top 25 collaborators of Shihui Yin. A scholar is included among the top collaborators of Shihui Yin 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 Shihui Yin. Shihui Yin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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