Chia-Chun Lin

440 citations
37 papers · 291 indexed · h-index 10
Topics
Advanced Memory and Neural Computing (10 papers)Quantum Computing Algorithms and Architecture (8 papers)Semiconductor materials and devices (7 papers)
Partner nations
TaiwanUnited StatesJapan

In The Last Decade

Chia-Chun Lin

34 papers receiving 277 citations

Peers

Chia-Chun Lin
Comparison fields: 5 of 41
  • Electrical and Electronic Engineering 156
  • Artificial Intelligence 128
  • Computational Theory and Mathematics 78
  • Atomic and Molecular Physics, and Optics 37
  • Hardware and Architecture 31
Replace Ramtin Zand with:
Ramtin Zand United States
Yuhao Wang Singapore
Dilip Vasudevan United States
Behjat Forouzandeh Iran
Yiming Chen China
Kamalika Datta India
Gurmohan Singh India
Ruizhe Cai United States
Sepehr Tabrizchi United States
Todor Mladenov United States
Chia-Chun Lin relative to Ramtin Zand United States Ramtin Zand's profile →
Citations per field
00.5×3.2×
Ramtin Zand · 1×
Citations per year

Countries citing papers authored by Chia-Chun Lin

Since Specialization
Citations

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

Fields of papers citing papers by Chia-Chun Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chia-Chun Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Chia-Chun Lin. A scholar is included among the top collaborators of Chia-Chun Lin 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 Chia-Chun Lin. Chia-Chun Lin 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
#WorkIndexed citations
1 5
2 10
3 2
4 2
5 1
6 6
7 6
8 10
9 1
10 23
11 8
12 9
13 6
14 1
15 21
16 18
17 19
18 4
19 9
20 13

About Chia-Chun Lin

Chia-Chun Lin is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering and Computational Theory and Mathematics, having authored 37 papers that have together received 291 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (10 papers), Quantum Computing Algorithms and Architecture (8 papers) and Semiconductor materials and devices (7 papers). The work is most often cited by research in Computational Theory and Mathematics (78 citations), Hardware and Architecture (31 citations) and Artificial Intelligence (128 citations). Chia-Chun Lin has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Niraj K. Jha, Amlan Chakrabarti, Chun-Yao Wang, Yung‐Chih Chen, Susmita Sur‐Kolay, Yung‐Hsien Wu, Chia‐Hsuan Chang, Jia‐Rong Wu, Yi-Ting Lin and Yun‐Ju Lee. Their work appears in journals such as Sensors, RSC Advances and IEEE Electron Device Letters.

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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