Jun Yao

46 papers receiving 566 citations

Peers

Jun Yao
Comparison fields: 5 of 102
  • Media Technology 108
  • Computer Vision and Pattern Recognition 109
  • Neuropsychology and Physiological Psychology 8
  • Aerospace Engineering 112
  • Health 38
Replace Sang-Woo Lee with:
Sang-Woo Lee South Korea
J. Apolinar Muñoz Rodríguez Spain
Huining Zhao China
Jiman Kim South Korea
Douglas Burleigh Russia
Sierra Hovet United States
Sangrok Lee South Korea
Hee-Joung Kim South Korea
James S. Goddard United States
Tianxiang Chen China
Jun Yao relative to Sang-Woo Lee South Korea Sang-Woo Lee's profile →
Citations per field
00.5×5.7×
Sang-Woo Lee · 1×
Citations per year

Countries citing papers authored by Jun Yao

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Yao. 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 Jun Yao. The network helps show where Jun Yao may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201588
2 201660
3 201656
4 201550
5 201730
6 201927
7 201423
8 201621
9 202220
10 202217
11 201516
12 201914
13 201412
14 201711
15 202210
16 20159
17 20159
18 20189
19 20169
20 20169

About Jun Yao

Jun Yao is a scholar working on Mechanical Engineering, Computer Vision and Pattern Recognition, Media Technology, Health and Electrical and Electronic Engineering, having authored 52 papers that have together received 588 indexed citations. Recurring topics across this work include Optical measurement and interference techniques (10 papers), Health disparities and outcomes (8 papers), Advanced Measurement and Metrology Techniques (6 papers), Structural Health Monitoring Techniques (6 papers), Image Processing Techniques and Applications (5 papers), Intergenerational Family Dynamics and Caregiving (5 papers), RFID technology advancements (5 papers) and Advanced Sensor and Energy Harvesting Materials (5 papers). The work is most often cited by research in Media Technology (108 citations), Computer Vision and Pattern Recognition (109 citations), Neuropsychology and Physiological Psychology (8 citations), Aerospace Engineering (112 citations) and Health (38 citations). Jun Yao has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Haiying Huang, Jeremiah Sanders, Saibun Tjuatja, Jubing Chen, Ankur Jain, Hong Miao, Man Yang, Yihao Zhou, Hao Wang and Xiong Chen. Their work appears in journals such as Optical Engineering, IEEE Sensors Journal, International Journal of Environmental Research and Public Health, Optics and Lasers in Engineering and Optics Express.

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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