Vahid Shalchyan

766 total citations
42 papers, 488 citations indexed

About

Vahid Shalchyan is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Signal Processing. According to data from OpenAlex, Vahid Shalchyan has authored 42 papers receiving a total of 488 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Cognitive Neuroscience, 24 papers in Cellular and Molecular Neuroscience and 10 papers in Signal Processing. Recurrent topics in Vahid Shalchyan's work include EEG and Brain-Computer Interfaces (35 papers), Neuroscience and Neural Engineering (23 papers) and Neural dynamics and brain function (16 papers). Vahid Shalchyan is often cited by papers focused on EEG and Brain-Computer Interfaces (35 papers), Neuroscience and Neural Engineering (23 papers) and Neural dynamics and brain function (16 papers). Vahid Shalchyan collaborates with scholars based in Iran, Denmark and Germany. Vahid Shalchyan's co-authors include Mohammad Reza Daliri, Dario Farina, Winnie Jensen, Imran Khan Niazi, Amirmasoud Ahmadi, Mads Jochumsen, Ivan Vujaklija, Ernest Nlandu Kamavuako, Hamid Reza Marateb and Ning Jiang and has published in prestigious journals such as Scientific Reports, Neuroscience and IEEE Access.

In The Last Decade

Vahid Shalchyan

40 papers receiving 475 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vahid Shalchyan Iran 12 382 227 151 62 50 42 488
Sheng Ge China 14 507 1.3× 149 0.7× 88 0.6× 89 1.4× 56 1.1× 69 645
Xingwei An China 14 488 1.3× 163 0.7× 55 0.4× 76 1.2× 83 1.7× 90 730
Florin Popescu Romania 9 583 1.5× 281 1.2× 142 0.9× 66 1.1× 115 2.3× 34 726
Natasha Padfield United Kingdom 6 412 1.1× 182 0.8× 70 0.5× 85 1.4× 101 2.0× 8 477
Attila Korik United Kingdom 8 281 0.7× 120 0.5× 80 0.5× 37 0.6× 33 0.7× 17 376
Weibo Yi China 15 576 1.5× 260 1.1× 134 0.9× 75 1.2× 123 2.5× 39 649
Yalda Shahriari United States 12 333 0.9× 131 0.6× 162 1.1× 21 0.3× 47 0.9× 41 502
Xinyi Yong Canada 11 391 1.0× 179 0.8× 96 0.6× 121 2.0× 58 1.2× 15 418
M. Thulasidas Singapore 5 587 1.5× 214 0.9× 214 1.4× 69 1.1× 75 1.5× 12 669
Yaqi Chu China 11 299 0.8× 113 0.5× 172 1.1× 38 0.6× 65 1.3× 31 460

Countries citing papers authored by Vahid Shalchyan

Since Specialization
Citations

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

Fields of papers citing papers by Vahid Shalchyan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vahid Shalchyan

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

All Works

20 of 20 papers shown
1.
Shalchyan, Vahid, et al.. (2025). Graph theory analysis based on cross frequency coupling methods in major depressive disorder: A resting state EEG study. Computers in Biology and Medicine. 198(Pt A). 111168–111168.
2.
Shalchyan, Vahid, et al.. (2024). Investigation of the impact of cross-frequency coupling on the assessment of depression severity through the analysis of resting state EEG signals. Biomedical Signal Processing and Control. 95. 106392–106392. 1 indexed citations
3.
Niazi, Imran Khan, et al.. (2024). Investigating the effects of chiropractic care on resting-state EEG of MCI patients. Frontiers in Aging Neuroscience. 16. 1406664–1406664. 2 indexed citations
4.
Shalchyan, Vahid, et al.. (2024). Improving Mean Covariance Matrix Estimation by Minimizing Within-class Dissimilarities Using Asymmetry of Kullback-Leibler Divergence in MI-Based BCI. IEEE Transactions on Industrial Informatics. 21(1). 128–135. 2 indexed citations
5.
Shalchyan, Vahid, et al.. (2024). A tensor decomposition scheme for EEG-based diagnosis of mild cognitive impairment. Heliyon. 10(4). e26365–e26365. 6 indexed citations
6.
Shalchyan, Vahid, et al.. (2023). Designing a Motion-Onset Visual-Evoked Potential-Based Brain–Computer Interface to Control a Computer Game. IEEE Transactions on Games. 16(2). 409–418. 3 indexed citations
7.
Shalchyan, Vahid, et al.. (2023). Decoding hand kinetics and kinematics using somatosensory cortex activity in active and passive movement. iScience. 26(10). 107808–107808. 5 indexed citations
8.
9.
Shalchyan, Vahid, et al.. (2022). Continuous Decoding of Hand Movement From EEG Signals Using Phase-Based Connectivity Features. Frontiers in Human Neuroscience. 16. 901285–901285. 13 indexed citations
10.
Moradi, Mohammad Hassan, Mohammad Bagher Shamsollahi, Ali Motie Nasrabadi, et al.. (2020). The 2017 and 2018 Iranian Brain–Computer Interface Competitions. Journal of Medical Signals & Sensors. 10(3). 208–216. 4 indexed citations
11.
Shalchyan, Vahid, et al.. (2020). Force decoding using local field potentials in primary motor cortex: PLS or Kalman filter regression?. Physical and Engineering Sciences in Medicine. 43(1). 175–186. 12 indexed citations
12.
Shalchyan, Vahid, et al.. (2020). Investigating the impact of mobile range electromagnetic radiation on the medial prefrontal cortex of the rat during working memory. Behavioural Brain Research. 391. 112703–112703. 10 indexed citations
13.
Shalchyan, Vahid, et al.. (2019). Adaptation effects of medial forebrain bundle micro-electrical stimulation. Bioengineered. 10(1). 78–86. 9 indexed citations
14.
Shalchyan, Vahid, et al.. (2019). Ratbot navigation using deep brain stimulation in ventral posteromedial nucleus. Bioengineered. 10(1). 250–260. 9 indexed citations
15.
Ganjali, Mojtaba & Vahid Shalchyan. (2019). Extracting Spatial Spectral Patterns from EEG Signals for Diagnosis of Mild Cognitive Impairment. 48(4). 1741–1752. 1 indexed citations
16.
Shalchyan, Vahid, et al.. (2019). Adaptive Artifact Removal From Intracortical Channels for Accurate Decoding of a Force Signal in Freely Moving Rats. Frontiers in Neuroscience. 13. 350–350. 14 indexed citations
17.
Shalchyan, Vahid, et al.. (2019). Upper limb complex movements decoding from pre-movement EEG signals using wavelet common spatial patterns. Computer Methods and Programs in Biomedicine. 183. 105076–105076. 43 indexed citations
18.
Vujaklija, Ivan, Vahid Shalchyan, Ernest Nlandu Kamavuako, et al.. (2018). Online mapping of EMG signals into kinematics by autoencoding. Journal of NeuroEngineering and Rehabilitation. 15(1). 21–21. 60 indexed citations
19.
Shalchyan, Vahid, et al.. (2016). Continuous Force Decoding from Local Field Potentials of the Primary Motor Cortex in Freely Moving Rats. Scientific Reports. 6(1). 35238–35238. 41 indexed citations
20.
Shalchyan, Vahid, Winnie Jensen, & Dario Farina. (2012). Spike Detection and Clustering With Unsupervised Wavelet Optimization in Extracellular Neural Recordings. IEEE Transactions on Biomedical Engineering. 59(9). 2576–2585. 39 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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