Gary Garcia‐Molina
- Cognitive Neuroscience top 2%
- Cellular and Molecular Neuroscience top 5%
- Experimental and Cognitive Psychology top 5%
- Human-Computer Interaction top 2%
- Signal Processing top 5%
- Co-authors
- Danhua ZhuJordi BiegerRonald M. AartsTsvetomira TsonevaGiulio TononiBrady A. RiednerMichele BellesiChiara Cirelli
- Topics
- EEG and Brain-Computer Interfaces (37 papers)Neural dynamics and brain function (21 papers)Sleep and Wakefulness Research (12 papers)
- Journals
- Scientific ReportsSensorsSLEEP
- Partner nations
- United StatesNetherlandsFinland
In The Last Decade
Gary Garcia‐Molina
50 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 75
- Cognitive Neuroscience 1.1k
- Cellular and Molecular Neuroscience 422
- Experimental and Cognitive Psychology 237
- Human-Computer Interaction 160
- Signal Processing 152
Countries citing papers authored by Gary Garcia‐Molina
This map shows the geographic impact of Gary Garcia‐Molina'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 Gary Garcia‐Molina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary Garcia‐Molina more than expected).
Fields of papers citing papers by Gary Garcia‐Molina
This network shows the impact of papers produced by Gary Garcia‐Molina. 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 Gary Garcia‐Molina. The network helps show where Gary Garcia‐Molina may publish in the future.
Co-authorship network of co-authors of Gary Garcia‐Molina
This figure shows the co-authorship network connecting the top 25 collaborators of Gary Garcia‐Molina. A scholar is included among the top collaborators of Gary Garcia‐Molina 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 Gary Garcia‐Molina. Gary Garcia‐Molina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 9 | |
| 9 | 8 | |
| 10 | 19 | |
| 11 | 20 | |
| 12 | 54 | |
| 13 | 17 | |
| 14 | 4 | |
| 15 | 30 | |
| 16 | 27 | |
| 17 | 35 | |
| 18 | Detection of high frequency steady state visual evoked potentials for Brain-computer interfaces | 20 |
| 19 | Automatic Determination of the Optimum Stimulation Frequencies in an SSVEP based BCI | 2 |
| 20 | Images Identification Based on Equivalence Classes | 3 |
About Gary Garcia‐Molina
Gary Garcia‐Molina is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Signal Processing, having authored 54 papers that have together received 1.3k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (37 papers), Neural dynamics and brain function (21 papers) and Sleep and Wakefulness Research (12 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Human-Computer Interaction (160 citations) and Cellular and Molecular Neuroscience (422 citations). Gary Garcia‐Molina has collaborated with scholars based in United States, Netherlands and Finland. Frequent co-authors include Danhua Zhu, Jordi Bieger, Ronald M. Aarts, Tsvetomira Tsoneva, Giulio Tononi, Brady A. Riedner, Michele Bellesi, Chiara Cirelli, Anton Nijholt and Vojkan Mihajlović. Their work appears in journals such as Scientific Reports, Sensors and SLEEP.
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.