A. Amalin Prince

653 total citations
51 papers, 434 citations indexed

About

A. Amalin Prince is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Signal Processing. According to data from OpenAlex, A. Amalin Prince has authored 51 papers receiving a total of 434 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Electrical and Electronic Engineering, 12 papers in Cognitive Neuroscience and 10 papers in Signal Processing. Recurrent topics in A. Amalin Prince's work include EEG and Brain-Computer Interfaces (10 papers), Machine Fault Diagnosis Techniques (7 papers) and Blind Source Separation Techniques (6 papers). A. Amalin Prince is often cited by papers focused on EEG and Brain-Computer Interfaces (10 papers), Machine Fault Diagnosis Techniques (7 papers) and Blind Source Separation Techniques (6 papers). A. Amalin Prince collaborates with scholars based in India, Singapore and Kuwait. A. Amalin Prince's co-authors include Anita Agrawal, Anita Agarwal, Rajamanickam Yuvaraj, Malathy Jawahar, F. Robert, Jac Fredo Agastinose Ronickom, M. Murugappan, Javeed Shaikh Mohammed, D. Raju and Shibu Clement and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and The International Journal of Advanced Manufacturing Technology.

In The Last Decade

A. Amalin Prince

48 papers receiving 423 citations

Peers

A. Amalin Prince

EEE

CSE

Y. Padma Sai India

Joël Karel Netherlands

Cheng‐Kai Lu Malaysia

Ali Jafari United States

Abhishek Gupta India

Abdullah Çavuşoğlu Türkiye

Kyoungwoo Lee South Korea

Jayanta Mukhopadhyay India

Wenkai Huang China

Y. Padma Sai India

A. Amalin Prince

122 ×1.1

144 ×1.6

50 ×0.7

EEE

60 ×1.3

15 ×0.3

CSE

Citations per year, relative to A. Amalin Prince A. Amalin Prince (= 1×) peers Y. Padma Sai

Countries citing papers authored by A. Amalin Prince

Since Specialization

Citations

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

Fields of papers citing papers by A. Amalin Prince

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Amalin Prince. 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 A. Amalin Prince. The network helps show where A. Amalin Prince may publish in the future.

Co-authorship network of co-authors of A. Amalin Prince

This figure shows the co-authorship network connecting the top 25 collaborators of A. Amalin Prince. A scholar is included among the top collaborators of A. Amalin Prince 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 A. Amalin Prince. A. Amalin Prince 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

Yuvaraj, Rajamanickam, et al.. (2025). Affective Computing for Learning in Education: A Systematic Review and Bibliometric Analysis. Education Sciences. 15(1). 65–65. 3 indexed citations

Sreeraj, Vanteemar S., et al.. (2025). Fine-Tuning EEG Channel Utilization for Emotionally Stimulated Biometric Authentication. IEEE Access. 13. 27537–27549. 3 indexed citations

Prince, A. Amalin, et al.. (2025). VCONV: A Convolutional Neural Network Accelerator for FPGAs. Electronics. 14(4). 657–657.

Jawahar, Malathy, et al.. (2025). LBPMobileNet-based novel and simple leather image classification method. Neural Computing and Applications. 37(33). 27575–27592. 2 indexed citations

Yuvaraj, Rajamanickam, et al.. (2024). A Machine Learning Framework for Classroom EEG Recording Classification: Unveiling Learning-Style Patterns. Algorithms. 17(11). 503–503. 4 indexed citations

Jawahar, Malathy, et al.. (2024). Vision Transformer-based Deep Learning Model for Leather Species Identification. 313–317.

Abirami, S., M. Kathiravan, Rajamanickam Yuvaraj, et al.. (2024). Automated Multi-Class Seizure-Type Classification System Using EEG Signals and Machine Learning Algorithms. IEEE Access. 12. 136524–136541. 3 indexed citations

Jawahar, Malathy, et al.. (2023). Learning species-definite features from digital microscopic leather images. Expert Systems with Applications. 224. 119971–119971. 8 indexed citations

Jawahar, Malathy, et al.. (2023). Auto-pore segmentation of digital microscopic leather images for species identification. Engineering Applications of Artificial Intelligence. 126. 107049–107049. 3 indexed citations

10.

Prince, A. Amalin, et al.. (2023). Low Valence Low Arousal Stimuli: An Effective Candidate for EEG-Based Biometrics Authentication System. Studies in health technology and informatics. 302. 257–261. 1 indexed citations

11.

Prince, A. Amalin, et al.. (2023). De-noising of microwave reflectometry signal using maximal overlap discrete wavelet packet transform for plasma density measurement. Measurement. 222. 113564–113564. 8 indexed citations

12.

Yuvaraj, Rajamanickam, et al.. (2023). Emotion Recognition from Spatio-Temporal Representation of EEG Signals via 3D-CNN with Ensemble Learning Techniques. Brain Sciences. 13(4). 685–685. 23 indexed citations

13.

Prince, A. Amalin, et al.. (2022). Time-Sliced Architecture for Efficient Accelerator to Detrend High-Definition Electroencephalograms. IEEE Transactions on Instrumentation and Measurement. 71. 1–9. 1 indexed citations

14.

Yuvaraj, Rajamanickam, et al.. (2021). Automated EEG pathology detection based on different convolutional neural network models: Deep learning approach. Computers in Biology and Medicine. 133. 104434–104434. 25 indexed citations

15.

Prince, A. Amalin, et al.. (2020). Low-Power Hardware Accelerator for Detrending Measured Biopotential Data. IEEE Transactions on Instrumentation and Measurement. 70. 1–9. 6 indexed citations

16.

Thakker, Rajesh A., et al.. (2020). Parameter Extraction of PSP MOSFET Model in Multi-core Zynq SoC Platform. Procedia Computer Science. 171. 1027–1036. 3 indexed citations

17.

Prince, A. Amalin, et al.. (2019). Design of configurable multi-mode trigger unit. Measurement. 139. 482–489. 13 indexed citations

18.

Prince, A. Amalin, et al.. (2017). Entropy‐based feature extraction and classification of vibroarthographic signal using complete ensemble empirical mode decomposition with adaptive noise. IET Science Measurement & Technology. 12(3). 350–359. 41 indexed citations

19.

Prince, A. Amalin, et al.. (2016). Feature selection and classification methodology for the detection of knee-joint disorders. Computer Methods and Programs in Biomedicine. 127. 94–104. 97 indexed citations

20.

Robert, F., Shibu Clement, Anita Agrawal, & A. Amalin Prince. (2014). Investigation of Microelectromechanical Switches for Next Generation DC Power Distribution System. International Journal of Emerging Electric Power Systems. 15(6). 591–605. 7 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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