Ming-Chun Tien

34 papers receiving 1.1k citations

Peers

Ming-Chun Tien
Comparison fields: 5 of 73
  • Electrical and Electronic Engineering 927
  • Atomic and Molecular Physics, and Optics 626
  • Computer Vision and Pattern Recognition 161
  • Artificial Intelligence 106
  • Biomedical Engineering 104
Replace Reza Kheradmand with:
Reza Kheradmand Iran
J. F. Heanue United States
Paul C. Mogensen Denmark
Hua‐Kuang Liu United States
Anlin Yi China
T. C. Strand United States
Mamoru Endo Japan
Werner Klaus Japan
Ken Tanizawa Japan
Lixia Xi China
Ming-Chun Tien relative to Reza Kheradmand Iran Reza Kheradmand's profile →
Citations per field
00.5×1.5×2.4×
Reza Kheradmand · 1×
Citations per year

Countries citing papers authored by Ming-Chun Tien

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Chun Tien

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming-Chun Tien

This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Chun Tien. A scholar is included among the top collaborators of Ming-Chun Tien 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 Ming-Chun Tien. Ming-Chun Tien 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 0
2 109
3 343
4 111
5 181
6 15
7 60
8 18
9 12
10
Silicon photonic devices for optoelectronic integrated circuits
2
11 45
12 1
13 20
14
Edge-coupled membrane terahertz photonic transmitters with high conversion efficiency
0
15 6
16 0
17 5
18 13
19 4
20 5

About Ming-Chun Tien

Ming-Chun Tien is a scholar working on Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 39 papers that have together received 1.2k indexed citations. Recurring topics across this work include Photonic and Optical Devices (19 papers), Photonic Crystals and Applications (6 papers) and Video Analysis and Summarization (5 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (626 citations), Electrical and Electronic Engineering (927 citations) and Computer Vision and Pattern Recognition (161 citations). Ming-Chun Tien has collaborated with scholars based in Taiwan, United States and Netherlands. Frequent co-authors include John E. Bowers, Daniel J. Blumenthal, Jared F. Bauters, Daoxin Dai, Martijn J. R. Heck, Paolo Pintus, Demis D. John, Arne Leinse, René Heideman and Tetsuya Mizumoto. Their work appears in journals such as Optics Letters, Optics Express and Applied Physics A.

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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2026