Yi-Chun Shih

1.7k citations
33 papers · 1.2k indexed · 1 hit paper · h-index 21

Yi-Chun Shih

33 papers receiving 1.2k citations

Hit Papers

16.4 An 89TOPS/W and 16.3TOPS/mm2 All-Digital SRAM-Based ...206202120262022202450100150200

Peers

Yi-Chun Shih
Comparison fields: 5 of 56
  • Hardware and Architecture 148
  • Electrical and Electronic Engineering 1.0k
  • Atomic and Molecular Physics, and Optics 248
  • Polymers and Plastics 71
  • Biomedical Engineering 171
Replace Huichu Liu with:
Huichu Liu United States
Guangjun Xie China
Liang Fang China
Aida Todri‐Sanial France
Ya‐Chin King Taiwan
Haralampos Pozidis Switzerland
Sumeet Kumar Gupta United States
Jaehoon Lee South Korea
Chia-Chen Kuo Taiwan
Chenyi Zhao China
Yi-Chun Shih relative to Huichu Liu United States Huichu Liu's profile →
Citations per field
00.5×1.7×
Huichu Liu · 1×
Citations per year

Countries citing papers authored by Yi-Chun Shih

Since Specialization
Citations

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

Fields of papers citing papers by Yi-Chun Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi-Chun Shih. 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 Yi-Chun Shih. The network helps show where Yi-Chun Shih may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Yi-Chun Shih, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yi-Chun Shih Line = papers co-authored together Yi-Chun Shih links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202331
2 202246
3 202124
4
16.4 An 89TOPS/W and 16.3TOPS/mm2 All-Digital SRAM-Based Full-Precision Compute-In Memory Macro in 22nm for Machine-Learning Edge Applicationsbreakdown →
2021206
5 20219
6 202123
7 201954
8 201841
9 201870
10 201597
11 201522
12 201418
13 201312
14 20102
15 20103
16 200914
17 200420
18 200334
19 200211
20 20022

About Yi-Chun Shih

Yi-Chun Shih is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics, having authored 33 papers that have together received 1.2k indexed citations. Recurring topics across this work include Ferroelectric and Negative Capacitance Devices (13 papers), Advanced Memory and Neural Computing (9 papers), Semiconductor materials and devices (8 papers), Magnetic properties of thin films (6 papers), Advancements in Semiconductor Devices and Circuit Design (4 papers), Low-power high-performance VLSI design (3 papers), Advanced Data Storage Technologies (3 papers) and Parallel Computing and Optimization Techniques (3 papers). The work is most often cited by research in Hardware and Architecture (148 citations), Electrical and Electronic Engineering (1.0k citations) and Atomic and Molecular Physics, and Optics (248 citations). Yi-Chun Shih has collaborated with scholars based in Taiwan, United States and Ukraine. Frequent co-authors include Brian Otis, Yu-Der Chih, Chia-Fu Lee, Po-Hao Lee, Tsung-Yung Jonathan Chang, King‐Fu Lin, Hsiao-Chi Hsieh, Jonathan Chang, Harry Chuang and Chieh-Pu Lo. Their work appears in journals such as Applied Physics Letters, Journal of Materials Chemistry A and IEEE Journal of Solid-State Circuits.

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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