Jinwei Xing

1.1k citations
9 papers · 181 · h-index 8

Impact in

Papers in

Jinwei Xing

9 papers receiving 177 citations

Peers

Jinwei Xing
Comparison fields: 5 of 45
  • Cognitive Neuroscience 90
  • Cellular and Molecular Neuroscience 40
  • Electrical and Electronic Engineering 111
  • Artificial Intelligence 58
  • Computer Vision and Pattern Recognition 17
Replace Amar Shrestha with:
Amar Shrestha United States
Adarsh Kumar Kosta United States
J. Camilo Vasquez Tieck Germany
Alan G. Millard United Kingdom
Jan Stuijt Netherlands
Guangzhi Tang Netherlands
Stanisław Woźniak Switzerland
Elisa Capecci New Zealand
Gregor Lenz France
Jinwei Xing relative to Amar Shrestha United States Amar Shrestha's profile →
Citations per field
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Amar Shrestha · 1×
Citations per year

Countries citing papers authored by Jinwei Xing

Since Specialization
Citations

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

Fields of papers citing papers by Jinwei Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Jinwei Xing, 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 Jinwei Xing Line = papers co-authored together Jinwei Xing links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 201861
2 202229
3 202123
4 201721
5 202016
6 202213
7 20239
8 20207
9 20222

About Jinwei Xing

Jinwei Xing is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Automotive Engineering, having authored 9 papers that have together received 181 indexed citations. Recurring topics across this work include Neural dynamics and brain function (6 papers), Advanced Memory and Neural Computing (3 papers), Memory and Neural Mechanisms (2 papers), Ferroelectric and Negative Capacitance Devices (1 paper), Cell Image Analysis Techniques (1 paper), Neuroscience and Neural Engineering (1 paper), EEG and Brain-Computer Interfaces (1 paper) and Neural Networks and Reservoir Computing (1 paper). The work is most often cited by research in Cognitive Neuroscience (90 citations), Cellular and Molecular Neuroscience (40 citations), Electrical and Electronic Engineering (111 citations), Artificial Intelligence (58 citations) and Computer Vision and Pattern Recognition (17 citations). Jinwei Xing has collaborated with scholars based in United States and China. Frequent co-authors include Jeffrey L. Krichmar, Nikil Dutt, Hirak J. Kashyap, Xinyun Zou, Michael Beyeler, Takashi Nagata, Emre Neftci, Huajin Tang, Hongying Li and Anup Das. Their work appears in journals such as Neural Networks, Frontiers in Neurorobotics, Proceedings of the National Academy of Sciences, Cognitive Computation and 2022 International Joint Conference on Neural Networks (IJCNN).

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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