M. Thulasidas
- Cognitive Neuroscience top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Biomedical Engineering
- Cellular and Molecular Neuroscience top 10%
- Human-Computer Interaction top 5%
- Co-authors
- Cuntai GuanJiankang WuRanganatha SitaramHaihong ZhangAkihiro IshikawaKōji ShimizuNiels BirbaumerYoko Hoshi
- Topics
- EEG and Brain-Computer Interfaces (4 papers)Neural dynamics and brain function (2 papers)Particle physics theoretical and experimental studies (2 papers)
- Journals
- NeuroImageNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentIEEE Transactions on Neural Systems and Rehabilitation Engineering
- Partner nations
- SingaporeUnited StatesGermany
In The Last Decade
M. Thulasidas
10 papers receiving 636 citations
Peers
Comparison fields: 5 of 58
- Cognitive Neuroscience 587
- Radiology, Nuclear Medicine and Imaging 216
- Biomedical Engineering 214
- Cellular and Molecular Neuroscience 214
- Human-Computer Interaction 89
Countries citing papers authored by M. Thulasidas
This map shows the geographic impact of M. Thulasidas'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 M. Thulasidas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Thulasidas more than expected).
Fields of papers citing papers by M. Thulasidas
This network shows the impact of papers produced by M. Thulasidas. 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 M. Thulasidas. The network helps show where M. Thulasidas may publish in the future.
Co-authorship network of co-authors of M. Thulasidas
This figure shows the co-authorship network connecting the top 25 collaborators of M. Thulasidas. A scholar is included among the top collaborators of M. Thulasidas 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 M. Thulasidas. M. Thulasidas 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 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 438 | |
| 8 | 202 | |
| 9 | 9 | |
| 10 | Robust classification of event-related potential for brain-computer interface | 8 |
| 11 | Search for the standard model Higgs boson at the LEP2 Collider near √s = 183 GeV | 4 |
| 12 | 2 |
About M. Thulasidas
M. Thulasidas is a scholar working on Nuclear and High Energy Physics, Cognitive Neuroscience and Human-Computer Interaction, having authored 12 papers that have together received 669 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (4 papers), Neural dynamics and brain function (2 papers) and Particle physics theoretical and experimental studies (2 papers). The work is most often cited by research in Cognitive Neuroscience (587 citations), Human-Computer Interaction (89 citations) and Cellular and Molecular Neuroscience (214 citations). M. Thulasidas has collaborated with scholars based in Singapore, United States and Germany. Frequent co-authors include Cuntai Guan, Jiankang Wu, Ranganatha Sitaram, Haihong Zhang, Akihiro Ishikawa, Kōji Shimizu, Niels Birbaumer, Yoko Hoshi, R. Barate and Weiran Xu. Their work appears in journals such as NeuroImage, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and IEEE Transactions on Neural Systems and Rehabilitation 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.