Aboozar Taherkhani

1.3k total citations · 1 hit paper
26 papers, 912 citations indexed

About

Aboozar Taherkhani is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Signal Processing. According to data from OpenAlex, Aboozar Taherkhani has authored 26 papers receiving a total of 912 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 9 papers in Electrical and Electronic Engineering and 8 papers in Signal Processing. Recurrent topics in Aboozar Taherkhani's work include Neural dynamics and brain function (7 papers), Advanced Memory and Neural Computing (6 papers) and Neural Networks and Reservoir Computing (5 papers). Aboozar Taherkhani is often cited by papers focused on Neural dynamics and brain function (7 papers), Advanced Memory and Neural Computing (6 papers) and Neural Networks and Reservoir Computing (5 papers). Aboozar Taherkhani collaborates with scholars based in United Kingdom, Iran and Iraq. Aboozar Taherkhani's co-authors include Georgina Cosma, T.M. McGinnity, Liam Maguire, Ammar Belatreche, Yuhua Li, Pouria Ahmadi, Vinayak Ashok Bharadi, Seyyed Ali Seyyedsalehi, Arash Mohammadi and Amir Homayoun Jafari‬ and has published in prestigious journals such as Energy Conversion and Management, Sensors and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Aboozar Taherkhani

24 papers receiving 880 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review of learning in biologically plausible spiking neural networks

2019 268 citations Aboozar Taherkhani, Ammar Belatreche et al. Neural Networks profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aboozar Taherkhani United Kingdom	11	413	329	277	136	111	26	912
Qiang Wu China	17	211 0.5×	313 1.0×	198 0.7×	168 1.2×	47 0.4×	47	1.0k
Xiaodong Ren China	14	177 0.4×	163 0.5×	333 1.2×	89 0.7×	166 1.5×	38	867
Jing Wen China	19	160 0.4×	181 0.6×	238 0.9×	381 2.8×	228 2.1×	92	1.2k
Saeed Bagheri Shouraki Iran	18	398 1.0×	453 1.4×	116 0.4×	274 2.0×	118 1.1×	100	1.1k
Chunbo Xiu China	14	227 0.5×	161 0.5×	125 0.5×	176 1.3×	46 0.4×	77	784
G. Jiménez Spain	20	925 2.2×	177 0.5×	440 1.6×	120 0.9×	483 4.4×	90	1.3k
M. J. E. Salami Malaysia	18	185 0.4×	223 0.7×	136 0.5×	185 1.4×	53 0.5×	101	964
N. Srinivasa United States	13	252 0.6×	131 0.4×	154 0.6×	194 1.4×	122 1.1×	35	597
Ahmad Ayatollahi Iran	18	249 0.6×	296 0.9×	237 0.9×	288 2.1×	105 0.9×	97	1.2k
Enzeng Dong China	17	205 0.5×	113 0.3×	333 1.2×	300 2.2×	113 1.0×	93	1.1k

Countries citing papers authored by Aboozar Taherkhani

Since Specialization

Citations

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

Fields of papers citing papers by Aboozar Taherkhani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aboozar Taherkhani

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

All Works

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20 of 20 papers shown

Taherkhani, Aboozar, et al.. (2025). Comparative Evaluation of Neural Networks and Transfer Learning for Predicting Mechanical Properties of 3D‐Printed Bone Scaffolds. Macromolecular Materials and Engineering. 310(10).

Taherkhani, Aboozar, et al.. (2024). PointCloud-At: Point Cloud Convolutional Neural Networks with Attention for 3D Data Processing. Sensors. 24(19). 6446–6446.

Taherkhani, Aboozar, Georgina Cosma, & T.M. McGinnity. (2023). A Deep Convolutional Neural Network for Time Series Classification with Intermediate Targets. SN Computer Science. 4(6). 6 indexed citations

Cosma, Georgina, et al.. (2020). Enhancing Prediction in Cyclone Separators through Computational Intelligence. 1–8. 3 indexed citations

Taherkhani, Aboozar, Georgina Cosma, & T.M. McGinnity. (2020). AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning. Neurocomputing. 404. 351–366. 187 indexed citations

Cosma, Georgina, et al.. (2020). Classifying Imbalanced Multi-modal Sensor Data for Human Activity Recognition in a Smart Home using Deep Learning. 1–8. 21 indexed citations

Taherkhani, Aboozar, Ammar Belatreche, Yuhua Li, et al.. (2019). A review of learning in biologically plausible spiking neural networks. Neural Networks. 122. 253–272. 268 indexed citations breakdown →

Taherkhani, Aboozar, Georgina Cosma, & T.M. McGinnity. (2018). Deep-FS: A feature selection algorithm for Deep Boltzmann Machines. Neurocomputing. 322. 22–37. 54 indexed citations

Cosma, Georgina, et al.. (2018). On-line voltage stability monitoring using an Ensemble AdaBoost classifier. Nottingham Trent University's Institutional Repository (Nottingham Trent Repository). 19. 253–259. 15 indexed citations

10.

Cosma, Georgina, et al.. (2018). Hand gesture recognition using an adapted convolutional neural network with data augmentation. Nottingham Trent University's Institutional Repository (Nottingham Trent Repository). 5–12. 47 indexed citations

11.

Taherkhani, Aboozar, Ammar Belatreche, Yuhua Li, & Liam Maguire. (2018). A Supervised Learning Algorithm for Learning Precise Timing of Multiple Spikes in Multilayer Spiking Neural Networks. IEEE Transactions on Neural Networks and Learning Systems. 29(11). 5394–5407. 72 indexed citations

12.

Taherkhani, Aboozar, Ammar Belatreche, Yuhua Li, & Liam Maguire. (2015). Multi-DL-ReSuMe: Multiple neurons Delay Learning Remote Supervised Method. University of Salford Institutional Repository (University of Salford). 1–7. 8 indexed citations

13.

Taherkhani, Aboozar, Ammar Belatreche, Yuhua Li, & Liam Maguire. (2014). A new biologically plausible supervised learning method for spiking neurons. University of Salford Institutional Repository (University of Salford). 11–16. 9 indexed citations

14.

Ahmadi, Pouria, et al.. (2012). Modeling and thermo-economic optimization of heat recovery heat exchangers using a multimodal genetic algorithm. Energy Conversion and Management. 58. 149–156. 61 indexed citations

15.

Taherkhani, Aboozar. (2011). Using Decision Tree Classifiers in Source Code Analysis to Recognize Algorithms: An Experiment with Sorting Algorithms. The Computer Journal. 54(11). 1845–1860. 10 indexed citations

16.

Taherkhani, Aboozar, Ari Korhonen, & Lauri Malmi. (2010). Recognizing Algorithms Using Language Constructs, Software Metrics and Roles of Variables: An Experiment with Sorting Algorithms. The Computer Journal. 54(7). 1049–1066. 7 indexed citations

17.

Seyyedsalehi, Seyyed Ali, et al.. (2010). Robust pattern recognition using chaotic dynamics in Attractor Recurrent Neural Network. 79. 1–6. 4 indexed citations

18.

Taherkhani, Aboozar, Seyyed Ali Seyyedsalehi, & Arash Mohammadi. (2008). Design of Chaotic Neural Network for Robust Phoneme Recognition. 69. 106–110. 3 indexed citations

19.

Taherkhani, Aboozar, et al.. (2008). Design of a chaotic neural network by using chaotic nodes and NDRAM network. 3500–3504. 4 indexed citations

20.

Mohammadi, Arash, Farshad Almasganj, Aboozar Taherkhani, & Farnoosh Naderkhani. (2007). Using Phoneme Segmentation in Conjunction with Missing Feature Approaches for Noise Robust Speech Recognition. 34. 297–301. 2 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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