Mingyu Song

475 total citations
31 papers, 211 citations indexed

About

Mingyu Song is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Mingyu Song has authored 31 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Electrical and Electronic Engineering, 5 papers in Cognitive Neuroscience and 5 papers in Artificial Intelligence. Recurrent topics in Mingyu Song's work include Advanced Fiber Laser Technologies (4 papers), Neural dynamics and brain function (4 papers) and Neural and Behavioral Psychology Studies (4 papers). Mingyu Song is often cited by papers focused on Advanced Fiber Laser Technologies (4 papers), Neural dynamics and brain function (4 papers) and Neural and Behavioral Psychology Studies (4 papers). Mingyu Song collaborates with scholars based in China, United States and South Korea. Mingyu Song's co-authors include Yael Niv, Fumin Zhang, Xinghua Qu, Angela Langdon, Jindong Wang, Brent E. Little, Wei Zhao, Wenfu Zhang, Wei Ji and Xin Ma and has published in prestigious journals such as Applied Physics Letters, The Journal of the Acoustical Society of America and Optics Letters.

In The Last Decade

Mingyu Song

27 papers receiving 199 citations

Peers

Mingyu Song
Comparison fields: 5 of 88
  • Electrical and Electronic Engineering 73
  • Atomic and Molecular Physics, and Optics 66
  • Instrumentation 35
  • Cognitive Neuroscience 34
  • Biomedical Engineering 26
Replace Yifan Zhao with:
Yifan Zhao United States
Taehwan Kim South Korea
Giora Yahav Israel
Diederik Paul Moeys Switzerland
Benjamin W. Avants United States
Florian Willomitzer United States
Lanxin Zhu China
Gregory Johnson United States
Chang Song United States
Robert C. Gibbons United States
Yifan Zhao United States View profile →
Citations per field, relative to Mingyu Song
Mingyu Song · 1×
Citations per year, relative to Mingyu Song
Mingyu Song · 1×

Countries citing papers authored by Mingyu Song

Since Specialization
Citations

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

Fields of papers citing papers by Mingyu Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingyu Song

This figure shows the co-authorship network connecting the top 25 collaborators of Mingyu Song. A scholar is included among the top collaborators of Mingyu Song 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 Mingyu Song. Mingyu Song 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 0
2 0
3 4
4 4
5 2
6 10
7 4
8 2
9 5
10
Using Recurrent Neural Networks to Understand Human Reward Learning
3
11 22
12
Learning what is relevant for rewards via value-based serial hypothesis testing.
2
13 12
14 13
15 12
16 5
17 20
18
Korean VLBI Network receiver optics for simultaneous multi-frequency observation
1
19 13
20
Reliability Improvement of Automatic Basal Cell Carcinoma Classifier with an Ambiguous Pattern Class
0

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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