Isabella Palamara

17 total papers · 586 total citations
8 papers, 396 citations indexed

About

Isabella Palamara is a scholar working on Cognitive Neuroscience, Molecular Biology and Signal Processing. According to data from OpenAlex, Isabella Palamara has authored 8 papers receiving a total of 396 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cognitive Neuroscience, 2 papers in Molecular Biology and 2 papers in Signal Processing. Recurrent topics in Isabella Palamara's work include EEG and Brain-Computer Interfaces (4 papers), Complex Systems and Time Series Analysis (2 papers) and Water Quality Monitoring Technologies (2 papers). Isabella Palamara is often cited by papers focused on EEG and Brain-Computer Interfaces (4 papers), Complex Systems and Time Series Analysis (2 papers) and Water Quality Monitoring Technologies (2 papers). Isabella Palamara collaborates with scholars based in Italy, United States and Netherlands. Isabella Palamara's co-authors include Francesco Carlo Morabito, Giuseppe Morabito, Domenico Labate, Fabio La Foresta, Alessia Bramanti, A. Lay-Ekuakille, Diego Caratelli, Harold Szu, Nadia Mammone and Mario Versaci and has published in prestigious journals such as Review of Scientific Instruments, IEEE Transactions on Instrumentation and Measurement and IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control.

In The Last Decade

Isabella Palamara

8 papers receiving 379 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Isabella Palamara	213	71	68	62	59	8	396
Stefan Schinkel	155 0.7×	92 1.3×	48 0.7×	47 0.8×	35 0.6×	10	380
Accardo Agostino	218 1.0×	62 0.9×	90 1.3×	80 1.3×	78 1.3×	6	356
Aleksandra Pidde	137 0.6×	60 0.8×	25 0.4×	27 0.4×	34 0.6×	6	335
Gemma Lancaster	142 0.7×	62 0.9×	33 0.5×	32 0.5×	64 1.1×	13	412
Á. Molina	82 0.4×	79 1.1×	51 0.8×	17 0.3×	102 1.7×	17	346
А. А. Овчинников	250 1.2×	21 0.3×	36 0.5×	19 0.3×	16 0.3×	14	405
Daniel T. Kaplan	90 0.4×	136 1.9×	72 1.1×	18 0.3×	106 1.8×	11	370
Tirdad Seifi	281 1.3×	66 0.9×	41 0.6×	141 2.3×	35 0.6×	13	426
R. Moddemeijer	74 0.3×	24 0.3×	109 1.6×	21 0.3×	13 0.2×	6	360
Ivan Dvořák	199 0.9×	124 1.7×	45 0.7×	42 0.7×	16 0.3×	9	384

Countries citing papers authored by Isabella Palamara

Since Specialization

Citations

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

Fields of papers citing papers by Isabella Palamara

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isabella Palamara

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

All Works

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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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