Austin J. Brockmeier
- Artificial Intelligence top 5%
- Cognitive Neuroscience top 5%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Cellular and Molecular Neuroscience
- Co-authors
- José C. Prı́ncipeSohan SethBilal FadlallahA. KeilLing LiJoseph T. FrancisJohn ChoiIl Memming Park
- Topics
- Neural dynamics and brain function (19 papers)EEG and Brain-Computer Interfaces (17 papers)Blind Source Separation Techniques (9 papers)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Austin J. Brockmeier
42 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Artificial Intelligence 291
- Cognitive Neuroscience 273
- Computer Vision and Pattern Recognition 170
- Biomedical Engineering 162
- Cellular and Molecular Neuroscience 112
Countries citing papers authored by Austin J. Brockmeier
This map shows the geographic impact of Austin J. Brockmeier'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 Austin J. Brockmeier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Austin J. Brockmeier more than expected).
Fields of papers citing papers by Austin J. Brockmeier
This network shows the impact of papers produced by Austin J. Brockmeier. 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 Austin J. Brockmeier. The network helps show where Austin J. Brockmeier may publish in the future.
Co-authorship network of co-authors of Austin J. Brockmeier
This figure shows the co-authorship network connecting the top 25 collaborators of Austin J. Brockmeier. A scholar is included among the top collaborators of Austin J. Brockmeier 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 Austin J. Brockmeier. Austin J. Brockmeier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 3 | |
| 6 | 37 | |
| 7 | 1 | |
| 8 | 11 | |
| 9 | 90 | |
| 10 | 33 | |
| 11 | 18 | |
| 12 | LEARNING AND EXPLOITING RECURRENT PATTERNS IN NEURAL DATA | 1 |
| 13 | 8 | |
| 14 | Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEEbreakdown → | 457 |
| 15 | 4 | |
| 16 | 3 | |
| 17 | 20 | |
| 18 | 10 | |
| 19 | A novel family of non-parametric cumulative based divergences for point processes | 4 |
| 20 | 1 |
About Austin J. Brockmeier
Austin J. Brockmeier is a scholar working on Computational Mathematics, Cognitive Neuroscience and Signal Processing, having authored 44 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (19 papers), EEG and Brain-Computer Interfaces (17 papers) and Blind Source Separation Techniques (9 papers). The work is most often cited by research in Computational Mathematics (16 citations), Health Informatics (23 citations) and Cognitive Neuroscience (273 citations). Austin J. Brockmeier has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include José C. Prı́ncipe, Sohan Seth, Bilal Fadlallah, A. Keil, Ling Li, Joseph T. Francis, John Choi, Il Memming Park, Mulugeta Semework and Sophia Ananiadou. Their work appears in journals such as NeuroImage, Sports Medicine and Current Opinion in Neurobiology.
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.