Long Miao

38 papers receiving 1.1k citations

Hit Papers

A programmable diffractive deep neural network based on a digital-coding metasurface array 2022 · 391 citations
3910+1+3Years since publication100200300

Peers

Long Miao
Comparison fields: 5 of 124
  • Electronic, Optical and Magnetic Materials 477
  • Acoustics and Ultrasonics 22
  • Aerospace Engineering 431
  • Sensory Systems 64
  • Aging 16
Replace Kwang‐Jin Kim with:
Kwang‐Jin Kim South Korea
Haijun Shen China
Mi Li China
Surya Pal Singh India
Li Quan China
Chen Zhao China
Yingli Zhang China
Seongwook Choi South Korea
Jiaxuan Wang China
Long Miao relative to Kwang‐Jin Kim South Korea Kwang‐Jin Kim's profile →
Citations per field
00.5×10×16×
Kwang‐Jin Kim · 1×
Citations per year

Countries citing papers authored by Long Miao

Since Specialization
Citations

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

Fields of papers citing papers by Long Miao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A programmable diffractive deep neural network based on a digital-coding metasurface array
Hit paper breakdown →
2022391
2
A wireless communication scheme based on space- and frequency-division multiplexing using digital metasurfaces
Hit paper breakdown →
2021331
3 202055
4 201945
5 202033
6 201928
7 202128
8 202325
9 202222
10 202021
11 202420
12 202419
13 202019
14 201719
15 202318
16 202117
17 202215
18 202112
19 20229
20 20219

About Long Miao

Long Miao is a scholar working on Molecular Biology, Sensory Systems, Surgery, Pulmonary and Respiratory Medicine and Cognitive Neuroscience, having authored 44 papers that have together received 1.2k indexed citations. Recurring topics across this work include Hearing, Cochlea, Tinnitus, Genetics (8 papers), Noise Effects and Management (5 papers), Hearing Loss and Rehabilitation (5 papers), Metamaterials and Metasurfaces Applications (4 papers), Microplastics and Plastic Pollution (4 papers), Pancreatic and Hepatic Oncology Research (4 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers) and Gallbladder and Bile Duct Disorders (3 papers). The work is most often cited by research in Electronic, Optical and Magnetic Materials (477 citations), Acoustics and Ultrasonics (22 citations), Aerospace Engineering (431 citations), Sensory Systems (64 citations) and Aging (16 citations). Long Miao has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Tie Jun Cui, Qiang Cheng, Xiao Zhou, Qiang Xiao, Qian Ma, Che Liu, Shi Jin, Jun Yan Dai, Lei Zhang and Ming Zheng Chen. Their work appears in journals such as Environmental Science and Pollution Research, Scientific Reports, Ceramics International, BioMed Research International and Ecotoxicology and Environmental Safety.

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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