Daniel Suma

583 total citations · 1 hit paper
9 papers, 433 citations indexed

About

Daniel Suma is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Daniel Suma has authored 9 papers receiving a total of 433 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cognitive Neuroscience, 4 papers in Cellular and Molecular Neuroscience and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Daniel Suma's work include EEG and Brain-Computer Interfaces (6 papers), Neuroscience and Neural Engineering (4 papers) and Neural dynamics and brain function (2 papers). Daniel Suma is often cited by papers focused on EEG and Brain-Computer Interfaces (6 papers), Neuroscience and Neural Engineering (4 papers) and Neural dynamics and brain function (2 papers). Daniel Suma collaborates with scholars based in United States, India and China. Daniel Suma's co-authors include Bin He, Jianjun Meng, Bradley J. Edelman, Claire A. Zurn, Bryan Baxter, Christopher C. Cline, Da Deng, James Stieger, Stephen A. Engel and Shuai Ye and has published in prestigious journals such as Cerebral Cortex, IEEE Transactions on Biomedical Engineering and ACS Sustainable Chemistry & Engineering.

In The Last Decade

Daniel Suma

9 papers receiving 428 citations

Hit Papers

Noninvasive neuroimaging enhances continuous neural track... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel Suma United States 7 355 215 116 84 53 9 433
Christopher C. Cline United States 10 547 1.5× 303 1.4× 139 1.2× 115 1.4× 72 1.4× 20 665
Loïc Botrel Germany 8 396 1.1× 152 0.7× 39 0.3× 62 0.7× 34 0.6× 16 432
Rachel M. Miriani United States 8 322 0.9× 268 1.2× 86 0.7× 15 0.2× 106 2.0× 8 467
Simona Bufalari Italy 6 362 1.0× 168 0.8× 68 0.6× 87 1.0× 45 0.8× 9 407
Debra Zeitlin United States 5 290 0.8× 182 0.8× 32 0.3× 72 0.9× 45 0.8× 6 309
Sacha Leinders Netherlands 7 439 1.2× 329 1.5× 122 1.1× 38 0.5× 63 1.2× 14 498
C. Guger Austria 2 412 1.2× 243 1.1× 84 0.7× 77 0.9× 59 1.1× 3 427
Sung-Phil Kim South Korea 9 341 1.0× 89 0.4× 124 1.1× 33 0.4× 275 5.2× 16 534
Léa Pillette France 8 225 0.6× 97 0.5× 44 0.4× 48 0.6× 37 0.7× 15 262

Countries citing papers authored by Daniel Suma

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Suma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Suma

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Suma. A scholar is included among the top collaborators of Daniel Suma 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 Daniel Suma. Daniel Suma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Suma, Daniel, et al.. (2022). Closed-loop motor imagery EEG simulation for brain-computer interfaces. Frontiers in Human Neuroscience. 16. 951591–951591. 2 indexed citations
2.
Hema, M.K., C.S. Karthik, Daniel Suma, et al.. (2022). Enchant O H⋅⋅⋅O interactions in hydrated 6-amino-2-methoxypyrimidin-4(3H)one resembles as water flow in the channel: Crystallographic and theoretical investigations. Journal of Molecular Structure. 1263. 133098–133098. 8 indexed citations
3.
Stieger, James, Stephen A. Engel, Daniel Suma, & Bin He. (2021). Benefits of deep learning classification of continuous noninvasive brain–computer interface control. Journal of Neural Engineering. 18(4). 46082–46082. 42 indexed citations
4.
Suma, Daniel, Jianjun Meng, Bradley J. Edelman, & Bin He. (2020). Spatial-temporal aspects of continuous EEG-based neurorobotic control. Journal of Neural Engineering. 17(6). 66006–66006. 13 indexed citations
5.
Jiang, Haiteng, Bin He, Xiaoli Guo, et al.. (2019). Brain–Heart Interactions Underlying Traditional Tibetan Buddhist Meditation. Cerebral Cortex. 30(2). 439–450. 25 indexed citations
6.
Edelman, Bradley J., Jianjun Meng, Daniel Suma, et al.. (2019). Noninvasive neuroimaging enhances continuous neural tracking for robotic device control. Science Robotics. 4(31). 271 indexed citations breakdown →
7.
Meng, Jianjun, et al.. (2018). Three-Dimensional Brain–Computer Interface Control Through Simultaneous Overt Spatial Attentional and Motor Imagery Tasks. IEEE Transactions on Biomedical Engineering. 65(11). 2417–2427. 46 indexed citations
8.
Suma, Daniel, et al.. (2018). Interdependence theory of tissue failure: bulk and boundary effects. Royal Society Open Science. 5(2). 171395–171395. 3 indexed citations
9.
Suma, Daniel & Da Deng. (2014). Facile Synthesis of Fe3O4@g-C Nanorods for Reversible Adsorption of Molecules and Absorption of Ions. ACS Sustainable Chemistry & Engineering. 3(1). 133–139. 23 indexed citations

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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