Runchun Wang

509 citations
28 papers · 299 · h-index 10

Impact in

Papers in

Runchun Wang

26 papers receiving 291 citations

Peers

Runchun Wang
Comparison fields: 5 of 30
  • Cognitive Neuroscience 160
  • Cellular and Molecular Neuroscience 111
  • Electrical and Electronic Engineering 256
  • Artificial Intelligence 78
  • Signal Processing 20
Replace X. Arreguit with:
X. Arreguit Switzerland
Daniel Ben Dayan Rubin United States
Kristofor D. Carlson United States
Stephen Nease United States
Mehdi Aghagolzadeh United States
Kshitij Dhoble New Zealand
Nuttapod Nuntalid Switzerland
Davis Barch United States
Vishwa Goudar United States
Man Yao China
Runchun Wang relative to X. Arreguit Switzerland X. Arreguit's profile →
Citations per field
00.5×10×20×29×
X. Arreguit · 1×
Citations per year

Countries citing papers authored by Runchun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Runchun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201356
2 201736
3 201425
4 201621
5 201716
6 201514
7 201114
8 201513
9 201411
10 20189
11 20149
12 20168
13 20217
14 20147
15 20117
16 20187
17 20127
18 20197
19 20186
20 20185

About Runchun Wang

Runchun Wang is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Artificial Intelligence and Signal Processing, having authored 28 papers that have together received 299 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (20 papers), Neural dynamics and brain function (11 papers), Neuroscience and Neural Engineering (10 papers), Neural Networks and Applications (7 papers), Hearing Loss and Rehabilitation (5 papers), Neural Networks and Reservoir Computing (5 papers), Speech and Audio Processing (4 papers) and Acoustic Wave Phenomena Research (4 papers). The work is most often cited by research in Cognitive Neuroscience (160 citations), Cellular and Molecular Neuroscience (111 citations), Electrical and Electronic Engineering (256 citations), Artificial Intelligence (78 citations) and Signal Processing (20 citations). Runchun Wang has collaborated with scholars based in Australia, India and United States. Frequent co-authors include André van Schaik, Tara Julia Hamilton, Jonathan Tapson, Chetan Singh Thakur, Gregory Cohen, Klaus M. Stiefel, Ying Xu, Alistair McEwan, Craig Jin and Saeed Afshar. Their work appears in journals such as IEEE Transactions on Circuits and Systems I Regular Papers, Frontiers in Neuroscience, Applied Sciences and IEEE Transactions on Biomedical Circuits and Systems.

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.

Explore authors with similar magnitude of impact