Mount-Learn Wu

571 citations
49 papers · 449 · h-index 12

Impact in

Papers in

Mount-Learn Wu

46 papers receiving 424 citations

Peers

Mount-Learn Wu
Comparison fields: 5 of 33
  • Surfaces, Coatings and Films 155
  • Electrical and Electronic Engineering 383
  • Atomic and Molecular Physics, and Optics 158
  • Condensed Matter Physics 45
  • Biomedical Engineering 115
Replace Juha Tommila with:
Juha Tommila Finland
F.S. Walters United States
Alex Hartsuiker Netherlands
Christof Klein Austria
Fanglu Lu United States
Pascal Xavier France
K. Seo South Korea
Yuzo Ono Japan
Mahmoud R. M. Atalla United States
J. Daleiden Germany
Mount-Learn Wu relative to Juha Tommila Finland Juha Tommila's profile →
Citations per field
00.5×1.5×2.0×
Juha Tommila · 1×
Citations per year

Countries citing papers authored by Mount-Learn Wu

Since Specialization
Citations

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

Fields of papers citing papers by Mount-Learn Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mount-Learn Wu. 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 Mount-Learn Wu. The network helps show where Mount-Learn Wu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200887
2 200628
3 199727
4 200924
5 201121
6 201018
7 200717
8 200914
9 201514
10 201213
11 200413
12 199612
13 200611
14 201011
15 200811
16 200610
17 200110
18 20099
19 20109
20 20128

About Mount-Learn Wu

Mount-Learn Wu is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Surfaces, Coatings and Films, Biomedical Engineering and Condensed Matter Physics, having authored 49 papers that have together received 449 indexed citations. Recurring topics across this work include Photonic and Optical Devices (39 papers), Semiconductor Lasers and Optical Devices (19 papers), Optical Coatings and Gratings (13 papers), Photonic Crystals and Applications (13 papers), GaN-based semiconductor devices and materials (7 papers), Advanced Fiber Optic Sensors (5 papers), Microwave Engineering and Waveguides (4 papers) and Advanced Photonic Communication Systems (4 papers). The work is most often cited by research in Surfaces, Coatings and Films (155 citations), Electrical and Electronic Engineering (383 citations), Atomic and Molecular Physics, and Optics (158 citations), Condensed Matter Physics (45 citations) and Biomedical Engineering (115 citations). Mount-Learn Wu has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Jenq-Yang Chang, Chih‐Ming Wang, Chien-Chieh Lee, Jui‐Ming Hsu, Ching-Ting Lee, Jin‐Wei Shi, F.-M. Kuo, Chia‐Chi Chang, Ching‐Cherng Sun and Wen–Feng Hsieh. Their work appears in journals such as IEEE Photonics Technology Letters, Optics Express, Journal of Lightwave Technology, Optics Letters and Japanese Journal of Applied Physics.

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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