M. Thulasidas

6.5k citations
12 papers · 669 · h-index 5

Impact in

Papers in

M. Thulasidas

10 papers receiving 636 citations

Peers

M. Thulasidas
Comparison fields: 5 of 58
  • Cognitive Neuroscience 587
  • Human-Computer Interaction 89
  • Cellular and Molecular Neuroscience 214
  • Radiology, Nuclear Medicine and Imaging 216
  • Signal Processing 69
Replace Yunjun Nam with:
Yunjun Nam South Korea
Hyohyeong Kang South Korea
Hammad Nazeer Pakistan
Soheil Borhani United States
Irene Sturm Germany
Shubham Dodia India
Seyyed Bahram Borgheai United States
Phattarapong Sawangjai Thailand
Laura Acqualagna Germany
M. Thulasidas relative to Yunjun Nam South Korea Yunjun Nam's profile →
Citations per field
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Yunjun Nam · 1×
Citations per year

Countries citing papers authored by M. Thulasidas

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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

All Works

12 of 12 papers shown
#Work
1 2006438
2 2006202
3 20059
4
Robust classification of event-related potential for brain-computer interface
20048
5
Search for the standard model Higgs boson at the LEP2 Collider near √s = 183 GeV
19994
6 19922
7 20072
8 20182
9 20201
10 20211
11 20220
12 20220

About M. Thulasidas

M. Thulasidas is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Information Systems, Nuclear and High Energy Physics and Cellular and Molecular Neuroscience, having authored 12 papers that have together received 669 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (4 papers), Particle Detector Development and Performance (2 papers), Neuroscience and Neural Engineering (2 papers), Advanced Clustering Algorithms Research (2 papers), Data Mining Algorithms and Applications (2 papers), Machine Learning and Data Classification (2 papers), Advanced Memory and Neural Computing (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), Cellular and Molecular Neuroscience (214 citations), Radiology, Nuclear Medicine and Imaging (216 citations) and Signal Processing (69 citations). M. Thulasidas has collaborated with scholars based in Singapore, Germany and France. Frequent co-authors include Cuntai Guan, Jiankang Wu, Yoko Hoshi, Kōji Shimizu, Akihiro Ishikawa, Ranganatha Sitaram, Niels Birbaumer, Haihong Zhang, R. Barate and Xiangyang Zhu. Their work appears in journals such as IEEE Transactions on Neural Systems and Rehabilitation Engineering, NeuroImage, International Journal of Modern Physics D, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and PubMed.

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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