Fariel Shafee

400 total citations
6 papers, 68 citations indexed

About

Fariel Shafee is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Fariel Shafee has authored 6 papers receiving a total of 68 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Statistical and Nonlinear Physics, 3 papers in Artificial Intelligence and 2 papers in Cognitive Neuroscience. Recurrent topics in Fariel Shafee's work include Neural dynamics and brain function (2 papers), Quantum Computing Algorithms and Architecture (2 papers) and Advanced Thermodynamics and Statistical Mechanics (1 paper). Fariel Shafee is often cited by papers focused on Neural dynamics and brain function (2 papers), Quantum Computing Algorithms and Architecture (2 papers) and Advanced Thermodynamics and Statistical Mechanics (1 paper). Fariel Shafee collaborates with scholars based in United States. Fariel Shafee's co-authors include and has published in prestigious journals such as Engineering Applications of Artificial Intelligence, IMA Journal of Applied Mathematics and Stochastics and Dynamics.

In The Last Decade

Fariel Shafee

4 papers receiving 64 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fariel Shafee United States	3	31	30	18	10	6	6	68
Fabien Viger France	3	16 0.5×	28 0.9×	4 0.2×	3 0.3×	3 0.5×	3	64
Tyge Tiessen Denmark	3	28 0.9×	31 1.0×	6 0.3×		2 0.3×	5	67
M. S. Centonze Italy	3	16 0.5×	11 0.4×	5 0.3×		3 0.5×	5	34
K. Ramachandra India	9	21 0.7×	7 0.2×	2 0.1×		18 3.0×	72	399
O. Pinazza Switzerland	4	2 0.1×	11 0.4×	14 0.8×	5 0.5×	1 0.2×	14	52
Lawrence Roy United States	5	9 0.3×	7 0.2×	5 0.3×		12 2.0×	12	47
Joël Bellaïche United States	9	9 0.3×	6 0.2×	8 0.4×	1 0.1×	3 0.5×	33	226
Simon M. Goodwin United Kingdom	7	21 0.7×	32 1.1×			6 1.0×	36	213
Aaron Tikuisis Canada	7	22 0.7×	32 1.1×			8 1.3×	16	167
Árpád Tóth Hungary	10	11 0.4×	7 0.2×			6 1.0×	24	217

Countries citing papers authored by Fariel Shafee

Since Specialization

Citations

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

Fields of papers citing papers by Fariel Shafee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

No nodes

All Works

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6 of 6 papers shown

1.

Shafee, Fariel. (2007). Lambert function and a new non-extensive form of entropy. IMA Journal of Applied Mathematics. 72(6). 785–800. 37 indexed citations

2.

Shafee, Fariel. (2007). Oligo-Parametric Hierarchical Structure of Complex Systems. NeuroQuantology. 5(1).

3.

Shafee, Fariel. (2007). Quantum Images and the Measurement Process.

4.

Shafee, Fariel. (2007). STOCHASTIC DYNAMICS OF NETWORKS WITH SEMICLASSICAL EXCITATIONS. Stochastics and Dynamics. 7(3). 403–416. 1 indexed citations

5.

Shafee, Fariel. (2006). Neural networks with quantum gated nodes. Engineering Applications of Artificial Intelligence. 20(4). 429–437. 26 indexed citations

6.

Shafee, Fariel. (2006). Information in entangled dynamic quantum networks. Microelectronics Journal. 37(11). 1321–1324. 4 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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