Meng-Lin Yu

58 papers receiving 936 citations

Peers

Meng-Lin Yu
Comparison fields: 5 of 116
  • Hepatology 115
  • Hardware and Architecture 62
  • Dermatology 56
  • Electrical and Electronic Engineering 330
  • Hematology 63
Replace Subrata Ghosh with:
Subrata Ghosh India
Weikun Hou China
Frédéric Sala United States
Hong Luo China
Kentaro Yoshioka Japan
Yu‐Chi Chen Taiwan
S. Horiguchi Japan
Kun‐Mao Chao Taiwan
Qingguo Wang United States
Tatsuya Mori Japan
Meng-Lin Yu relative to Subrata Ghosh India Subrata Ghosh's profile →
Citations per field
00.5×10×15.5×
Subrata Ghosh · 1×
Citations per year

Countries citing papers authored by Meng-Lin Yu

Since Specialization
Citations

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

Fields of papers citing papers by Meng-Lin Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Meng-Lin Yu, 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 Meng-Lin Yu Line = papers co-authored together Meng-Lin Yu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1980116
2 200291
3 200283
4 200272
5 199768
6 199547
7 198543
8 199341
9 199140
10 198438
11 200237
12 199033
13 198429
14 201126
15 197722
16 202320
17 197818
18 197716
19 200914
20 199513

About Meng-Lin Yu

Meng-Lin Yu is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture, Atomic and Molecular Physics, and Optics, Molecular Biology and Artificial Intelligence, having authored 61 papers that have together received 1.0k indexed citations. Recurring topics across this work include Optical Network Technologies (7 papers), Advanced Fiber Laser Technologies (7 papers), VLSI and Analog Circuit Testing (6 papers), Low-power high-performance VLSI design (6 papers), Hepatitis B Virus Studies (4 papers), Advancements in PLL and VCO Technologies (4 papers), Platelet Disorders and Treatments (4 papers) and Photonic Crystal and Fiber Optics (3 papers). The work is most often cited by research in Hepatology (115 citations), Hardware and Architecture (62 citations), Dermatology (56 citations), Electrical and Electronic Engineering (330 citations) and Hematology (63 citations). Meng-Lin Yu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Gordon Guroff, J.S. Finlayson, N. Tolson, Leilei Song, C. J. McKinstrie, Govind P. Agrawal, Alan Heath, K. Azadet, Wu-Tung Cheng and J W Shih. Their work appears in journals such as Vox Sanguinis, Journal of Neurochemistry, Journal of the Optical Society of America B, IEEE Transactions on Visualization and Computer Graphics 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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