Xiaorong Gao

1.5k citations
20 papers · 1.1k indexed · 1 hit paper · h-index 9

Xiaorong Gao

17 papers receiving 1.1k citations

Hit Papers

Design and implementation of a brain-computer interface w...6272002202620102018200400600

Peers

Xiaorong Gao
Comparison fields: 5 of 68
  • Cognitive Neuroscience 1.1k
  • Cellular and Molecular Neuroscience 720
  • Human-Computer Interaction 207
  • Signal Processing 205
  • Electrical and Electronic Engineering 252
Replace B. Obermaier with:
B. Obermaier Austria
S.G. Mason Canada
Yangyang Miao China
Bingchuan Liu China
Reza Abiri United States
William A. Sarnacki United States
Hohyun Cho South Korea
C. Guger Austria
Pramod Gaur India
Xiaorong Gao relative to B. Obermaier Austria B. Obermaier's profile →
Citations per field
00.5×4.6×
B. Obermaier · 1×
Citations per year

Countries citing papers authored by Xiaorong Gao

Since Specialization
Citations

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

Fields of papers citing papers by Xiaorong Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20251
4 20242
5 20242
6 20241
7 20241
8 20230
9 202318
10 20222
11 20222
12 202210
13 202111
14 20147
15 201465
16 201315
17 2008329
18 200831
19 20058
20
Design and implementation of a brain-computer interface with high transfer ratesbreakdown →
2002627

About Xiaorong Gao

Xiaorong Gao is a scholar working on Cognitive Neuroscience, Human-Computer Interaction and Cellular and Molecular Neuroscience, having authored 20 papers that have together received 1.1k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (12 papers), Neuroscience and Neural Engineering (8 papers), Neural dynamics and brain function (5 papers), Advanced Memory and Neural Computing (5 papers), Gaze Tracking and Assistive Technology (3 papers), Advanced biosensing and bioanalysis techniques (3 papers), Visual perception and processing mechanisms (2 papers) and Biosensors and Analytical Detection (2 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Cellular and Molecular Neuroscience (720 citations) and Human-Computer Interaction (207 citations). Xiaorong Gao has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Shangkai Gao, Yijun Wang, Bo Hong, Chuan Jia, Yijun Wang, Xiaogang Chen, Tzyy‐Ping Jung, Masaki Nakanishi, Fei Meng and Hui Zhong. Their work appears in journals such as Chemical Communications, ACS Applied Materials & Interfaces and IEEE Transactions on Biomedical Engineering.

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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