Ming Ni

672 total citations · 1 hit paper
30 papers, 409 citations indexed

About

Ming Ni is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Physiology. According to data from OpenAlex, Ming Ni has authored 30 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Atomic and Molecular Physics, and Optics, 8 papers in Electrical and Electronic Engineering and 7 papers in Physiology. Recurrent topics in Ming Ni's work include Quantum and electron transport phenomena (9 papers), Advancements in Semiconductor Devices and Circuit Design (8 papers) and Dementia and Cognitive Impairment Research (7 papers). Ming Ni is often cited by papers focused on Quantum and electron transport phenomena (9 papers), Advancements in Semiconductor Devices and Circuit Design (8 papers) and Dementia and Cognitive Impairment Research (7 papers). Ming Ni collaborates with scholars based in China, United States and Australia. Ming Ni's co-authors include Qing He, Zhenhua Zhang, Jing Gao, Qiang Xie, Xinyi Lv, Feng Gao, Guilei Wang, Hai-Ou Li, Gang Cao and Guo‐Ping Guo and has published in prestigious journals such as Physical Review Letters, Nano Letters and Applied Physics Letters.

In The Last Decade

Ming Ni

28 papers receiving 393 citations

Hit Papers

A deep learning approach for detecting traffic accidents ... 2017 2026 2020 2023 2017 50 100 150 200

Peers

Ming Ni
Comparison fields: 5 of 97
  • Building and Construction 133
  • Artificial Intelligence 105
  • Transportation 65
  • Safety, Risk, Reliability and Quality 59
  • Electrical and Electronic Engineering 58
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Shengkun Xie Canada
Muhammad Asim Saleem China
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Sina Khanmohammadi United States View profile →
Citations per field, relative to Ming Ni
Ming Ni · 1×
Citations per year, relative to Ming Ni
Ming Ni · 1×

Countries citing papers authored by Ming Ni

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Ni

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Ni. A scholar is included among the top collaborators of Ming Ni 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 Ni. Ming Ni 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
# Work Indexed citations
1 1
2 2
3 1
4 7
5 1
6 0
7 2
8 23
9 10
10 1
11 4
12 6
13 13
14 1
15 32
16 4
17 1
18
A deep learning approach for detecting traffic accidents from social media data breakdown →
246
19
[Case-control study on earlier medial tibial pain after total knee arthroplasty].
1
20 1

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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