Publications

Prof. Kasabov is a prolific publisher of books, journal papers, conference proceedings and has several patents to his name.

Here we have listed some of the recent and relevant publications from the last years.

Full lists of his publications can be found on:

Professor Kasabov’s AUT Homepage

Google Scholar

ResearchGate

AUT Knowledge Engineering and Discovery Research Institute (KEDRI)

Patents

  • N.Kasabov, Data Analysis and Predictive Systems and Related Methodologies, US patent 9,002,682 B2, 7 April 2015. 

  • N.Kasabov, V.Feigin, Z.Hou, Y.Chen, Improved method and system for predicting outcomes based on spatio/spectro-temporal data, PCT patent WO2015/030606 A2, US2016/0210552 A1. Granted/Publication date: 21 July 2016.  

Books

Edited Scientific Books

  • P.Koprinkova-Hristova, N. Kasabov (Eds) Artificial Intelligence: Methodology, Systems, and Applications 19th International Conference, AIMSA 2024 Varna, Bulgaria, September 18–20, 2024 Proceedings, Lecture Notes in Artificial Intelligence, ISBN 978-3-031-81541-6, ISBN 978-3-031-81542-3 (eBook) https://doi.org/10.1007/978-3-031-81542-3.

Books Chapters

  • Predictive and Explainable Modelling in Economics on the Case Study of Remittance Prediction Using the NeuDen AI Computational Architecture," Chapter 6 in: P.Koprinkova-Hristova and N.K.Kasabov (eds)  “Artificial Intelligence: Methodology, Systems, and Applications”, AIMSA’,24, Varna, 18-20 September, Springer Nature LNAI 15462, pp.1-16, 2025.

  • Kasabov, N.K. (2024). STAM-SNN: Spatio-Temporal Associative Memory in Brain-Inspired Spiking Neural Networks: Concepts and Perspectives. In: Kovács, L., Haidegger, T., Szakál, A. (eds) Recent Advances in Intelligent Engineering. Topics in Intelligent Engineering and Informatics, vol 18. Springer, https://doi.org/10.1007/978-3-031-58257-8_1

  • Kasabov, N. (2024) Brain-inspired evolving and spiking connectionist systems, Chapter 8  in:  “Artificial intelligence in the age of neural networks and brain computing”, edited by Robert Kozma, Cesare Alippi, Yoonsuck Choe, Francesco Carlo Morabito, Academic Press, Elsevier, pp.145-171, https://doi.org/10.1016/B978-0-323-96104-2.00007-5, https://www.sciencedirect.com/science/article/abs/pii/B9780323961042000075?via%3Dihub, ISBN 978-0-323-96104-2.

  • Ravi Kumar Jha, Nikola Kasabov, Damien Coyle, Saugat Bhattacharyya, and Girijesh Prasad, Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data, Springer LNCS, Proc.ICONIP 2024. 

Preprints

  • Kasabov, N.K.; Yang, A.; Abouhassan, I.; Chace, C., Kassabova, A.; Lappas, T.: eXCube1: Explainable Neuromorphic Framework for Modelling Conscious Perception of Stimuli from fMRI Data, Preprint, https://doi.org/10.20944/preprints202604.0605.v1

  • Nikola Kirilov Kasabov*, Alexander Yang , Zhaoxin Wang , Iman Abouhassan , Assia Nikolova Kassabova , Teodoros Lappas, eXCube2: Explainable Brain-Inspired Spiking Neural Network Framework for Emotion Recognition from Audio-, Visual- and Multimodal Audio-Visual Data Posted Date: 13 February 2026 doi: 10.20944/preprints202602.1058.v1 https://doi.org/10.20944/preprints202602.1058.v1.  

  • Nida Shahab; Maryam Doborjeh; Nikola Kasabov, Brain-inspired Spiking Neural Network Frameworks for Multimodal Data Integration and Spatiotemporal Pattern Discovery: A Case Study on EEG-fMRI Data Preprint, DOI: 10.2139/ssrn.6381378

  • R.Jha, N.Kasabov, G.Prasad, S.Bathacharia, D.Coyle, A Hybrid Spiking Neural Network-Quantum Classifier Framework: A Case Study Using EEG Data, 21 March 2025, preprint, Research Square, https://doi.org/10.21203/rs.3.rs-6173906/v1

  • Ravi , N. Kasabov et al, (2023). From Quantum Computing to Quantum-inspired Computation for Neuromorphic Advancement – A Survey. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.24053250.v1 

  • AbouHassan, Iman; Kasabov, Nikola; Bankar, Tanmay; Garg, Rishabh; Sen Bhattacharya, Basabdatta (2023). PAMeT-SNN: Predictive Associative Memory for Multiple Time Series based on Spiking Neural Networks with Case Studies in Economics and Finance.  TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.24063975.v1.

  • Iman AbouHassan, Nikola K. Kasabov, Vinayak G.M. Jagtap, Parag Kulkarni, Spiking neural networks for predictive and explainable modelling of multimodal streaming data on the Case Study of Financial Time Series Data and on-line news, SREP, Springer-Nature, Sci Rep 13, 18367 (2023). https://doi.org/10.1038/s41598-023-42605-0 (pre-print on Research Square, https://www.researchsquare.com/article/rs-2262084/v1)

  • Samaneh Alsadat Saeedinia, Mohammad Reza Jahed Motlagh, Abbas Tafakhori, Nikola Kirilov Kasabov, Diagnostic biomarker discovery from brain EEG data with LSTM, reservoir-SNN and NeuCube: Methods and a pilot study on epilepsy vs migraine,  IEEE archive,  https://doi.org/10.36227/techrxiv.23514486.v1.

  • Kasabov, Nikola (2023). STAM-SNN: Spatio-Temporal Associative Memories in Brain-inspired Spiking Neural Networks: Concepts and Perspectives. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.23723208.v1

  • Xuanle Zhou, Maryam Doborjeh, Nikola Kirilov Kasabov, Zohreh Doborjeh, Integrating Local STDP and Global Backpropagation Learning Using Spike-Time and Spike-Rate Representations for Improved Classification of Spatiotemporal Data in the NeuCube Brain Inspired Evolving Spiking Neural Network Architecture: A Case Study on EEG Brain Data, January 2023, preprint, https://DOI.org/10.2139/ssrn.4617064.

Refereed Journal Articles

2026

  • Kasabov, N.K.; Yang, A.; Wang, Z.; Abouhassan, I.; Kassabova, A.; Lappas, T. eXCube2: Explainable Brain-Inspired Spiking Neural Network Framework for Emotion Recognition from Audio, Visual and Multimodal Audio–Visual Data. Biomimetics 2026, 11, 208. https://doi.org/10.3390/biomimetics11030208

  • Jha, N. Kasabov et al, Comparative Performance Analysis of Quantum Feature Maps for Quantum Kernel-based Machine Learning, Scientific Reports, February 2026,  16 (1), https://doi.org/10.1038/s41598-026-39392-9

2025

  • S.Zhou et al N. Kasabov, TSPFusion: Text-guided semantic perception for infrared and visible image fusion, Infrared Physics and Technology, Elsevier, Dec. 2025, INFPHY_106324.

  • Rusev, G.; Yordanov, S.; Nedelcheva, S.; Banderov, A.; Lafaye de Micheaux, H.; Sauter-Starace, F.; Aksenova, T.; Koprinkova-Hristova, P.; Kasabov, N. NEuroMOrphic Neural-Response Decoding System for Adaptive and Personalized Neuro-Prosthetics’ Control, Biomimetics 2025, 10, 518, https://doi.org/10.3390/biomimetics10080518

  • Jha, R.K., Kasabov, N., Bhattacharyya, S. et al. A hybrid spiking neural network - quantum framework for spatio-temporal data classification: a case study on EEG data. EPJ Quantum Technol. 12, 130 (2025). https://doi.org/10.1140/epjqt/s40507-025-00443-1

  • S. -A. Saeedinia, M. -R. Jahed-Motlagh, N. K. Kasabov and A. Tafakhori, "New Eigenvalue-Based Analysis for Precise Limit Cycle Stability Assessment in a Two-State Epileptor Model," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 55, no. 3, pp. 2062-2072, March 2025, doi: https://doi.org/10.1109/TSMC.2024.3517620.

  • Jia Lei, Jiawei Li, Jinyuan Liu, Bin Wang,  Shihua Zhou, Qiang Zhang, Xiaopeng Wei, Nikola K. Kasabov, "MLFuse: Multi-scenario Feature Joint Learning for Multi-Modality Image Fusion", IEEE Trans. Multimedia, 2025, https://ieeexplore.ieee.org/document/10856398.

  • Georgi Rusev, Svetlozar Yordanov, Simona Nedelcheva, Alexander Banderov, Fabien Sauter-Starace, Petia Koprinkova-Hristova *, Nikola Kasabov *, Decoding brain signals in a neuromorphic framework for a personalized adaptive control of human prosthetics, 2025, Biomimetics 2025, 10(3), 183;  https://doi.org/10.3390/biomimetics10030183

  • Yang, A.H.X., Galán-Augé, C., Kasabov, N.K., Cakmak, Y.,  Machine learning-guided high-definition transcranial direct current stimulation prevents cybersickness. Virtual Reality 29, 94 (2025). https://doi.org/10.1007/s10055-025-01160-x

  • Garcia-Palencia, O.; Fernandez, J.; Shim, V.; Kasabov, N.K.; Wang, A.; the Alzheimer’s Disease Neuroimaging Initiative. Spiking Neural Networks for Multimodal Neuroimaging: A Comprehensive Review of Current Trends and the NeuCube Brain-Inspired Architecture. Bioengineering 2025, 12, 628. https://doi.org/10.3390/bioengineering12060628, 

  • Khan A, Shim V, Fernandez J, Kasabov NK and Wang A (2025) Review of deep learning models with Spiking Neural Networks for modeling and analysis of multimodal neuroimaging data. Front. Neuroscience, 19:1623497. doi: https://doi.org/10.3389/fnins.2025.1623497.

  • Calude, C.S.; Gladding, P.; Henderson, A.; Kasabov, N. SAIN: Search-And-INfer, a Mathematical and Computational Framework for Personalised Multimodal Data Modelling with Applications in Healthcare. Algorithms 2025, 18, 605. https://doi.org/10.3390/a18100605

  • Hafezi Fard, M.; Petrova, K.; Kasabov, N.K.; Wang, G.Y. Modeling the Effect of Prior Knowledge on Memory Efficiency for the Study of Transfer of Learning: A Spiking Neural Network Approach. Big Data Cogn. Comput. 2025, 9, 173. https://doi.org/10.3390/bdcc9070173

2024

2023

  • Xiangyang Ning, Qing Dong, Shihua Zhou,  Qiang Zhang, Nikola K. Kasabov, Construction of new 5D Hamiltonian conservative hyperchaotic system and its application in image encryption, Nonlinear Dynamics, Springer-Nature, 2023,  https://doi:10.1007/s111071-023-08866-0

  • Samuel Ming Xuan Tan,  Jie Yin Yee, Sugam Budhraja, Balkaran Singh, Zohreh Doborjeh, Maryam Doborjeh, Nikola Kasabov, Edmund Lai, Alexander Sumich, Jimmy Lee, Wilson Wen Bin Goh, RNA-sequencing of peripheral whole blood of individuals at ultra-high-risk for psychosis – A longitudinal perspective, Asian Journal of Psychiatry, Elsevier, 89 (2023) 103796,  https://doi.org/10.1016/j.ajp.2023.103796

  • Qing Dong, Shihua  Zhou, Qiang Zhang, Nikola K. Kasabov,  A new five-dimensional non-Hamiltonian conservative hyperchaos system with multistability and transient properties, Chaos, Solitons and Fractals ,175 (2023) 113998,  https://doi.org/10.1016/j.chaos.2023.113998. 

  • Maciag, Piotr; Bembenik, Robert; Piekarzewicz Aleksandra,  Del Ser Lorente, Javier; Lopez Lobo, Jesus; Nikola Kasabov;, Effective Air Pollution Prediction by Combining Time Series Decomposition with Stacking and Bagging Ensembles of Evolving Spiking Neural Networks, Environmental Modelling and Software, vol.170, on line: 16.10.2023, Dec 2023, 105851,  https://doi.org/10.1016/j.envsoft.2023.105851.

  •  Nikola K. Kasabov, Helena Bahrami, Maryam Doborjeh, Alan Wang, Brain Inspired Spatio-Temporal Associative Memories for Neuroimaging Data: EEG and fMRI,  Bioengineering 2023, MDPI 10(12), 1341 https://doi.org/10.3390/bioengineering10121341, www.mdpi.com/journal/bioengineering (OA);  

  • S. Song, Z. Jia, J. Yang and N. Kasabov, "Image Segmentation Based on Fuzzy Low-Rank Structural Clustering," in IEEE Transactions on Fuzzy Systems, vol. 31, no. 7, pp. 2153-2166, July 2023, doi: , https://doi.org/10.1109/TFUZZ.2022.3220925.

  • Grace Wen, Vickie Shim, Samantha Jane Holdsworth, Justin Fernandez, Miao Qiao, Nikola Kasabov, Alan Wang Artificial Intelligence for Brain MRI Data Harmonization: A Systematic Review, Bioengineering, 10(4):397, Publisher MDPI, No.2259748, 2023, https://doi.org/10.3390/bioengineering10040397.

  • J. Li, J. Liu, S. Zhou, Q. Zhang and N. K. Kasabov, "Learning a Coordinated Network for Detail-Refinement Multiexposure Image Fusion," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 33, no. 2, pp. 713-727, Feb. 2023, doi: https://doi.org/10.1109/TCSVT.2022.3202692. 

  • Zohreh Doborjeh, Maryam Doborjeh, Alexander Sumich, Balkaran Singh, Alexander Merkin, Sugam Budhraja, Wilson Wen Bin Goh, Edmund Lai, Margaret Williams, Samuel Tan, Jimmy Lee, and Nikola Kasabov, Investigation of Social and Cognitive Predictors in Non-Transition Ultra-High-Risk’ Individuals for Psychosis Using Spiking Neural Networks, Schizophrenia, 9, 10 (2023), https://doi.org/10.1038/s41537-023-00335-2 (OA) 

  • Wei Zhang, Zhenhong Jia, Jie Yang, Nikola K. Kasabov, A dual channel decomposition and remapping fusion model for low illumination images with a wide field of view, Signal Processing: Image Communication, Elsevier, Vol. 113, 2023, 116925, ISSN 0923-5965, https://doi.org/10.1016/j.image.2023.116925.

  • Jiawei Lia, Jinyuan Liub, Shihua Zhoua, Qiang Zhang and Nikola K.Kasabov, Infrared and visible image fusion based on residual dense network and gradient loss, Infrared Physics and Technology , vol.128, Jan.2023, 104486, https://doi.org/10.1016/j.infrared.2022.104486.

  • Balkaran Singh, Maryam Doborjeh, Zohreh Doborjeh, Sugam Budhraja, Samuel Tan, Alexander Sumich, Wilson Goh, Jimmy Lee, Edmund Lai, Nikola Kasabov, Constrained Neuro Fuzzy Inference Methodology for Explainable Personalised Modelling with Applications on Gene Expression Data, Scientific Reports, 13-456, 2023, https://doi.org/10.1038/s41598-022-27132-8, 2023 . 

  • Kasabov, Nikola; Tan, Yongyao Tan; Doborjeh, Maryam; Tu, Enmei; Yang, Jie; Goh, Wilson; Lee, Jimmy  (2023): Transfer Learning of Fuzzy Spatio-Temporal Rules in the NeuCube Brain-Inspired Spiking Neural Network: A Case Study on EEG Spatio-temporal Data. IEEE Transactions on Fuzzy Systems, vol.31, issue 12, Dec.2023, 4542-4552, DOI: https://doi.org/10.1109/TFUZZ.2023.3292802, https://ieeexplore.ieee.org/document/10175605.

  • Martinez Seras Aitor, Del Ser Lorente Javier, Lopez Lobo Jesus, Pablo Garcia Bringas, Nikola Kasabov,  A Novel Out-of-Distribution Detection Approach for Spiking Neural Networks: Design, Fusion, Performance Evaluation and Explainability", Information Fusion, vol.100, Dec. 2023, 101943, https://doi.org/10.1016/j.inffus.2023.101943.

  • Iman AbouHassan, Nikola K. Kasabov, Vinayak G.M. Jagtap, Parag Kulkarni, Spiking neural networks for predictive and explainable modelling of multimodal streaming data on the Case Study of Financial Time Series Data and on-line news, SREP, Springer-Nature, Sci Rep 13, 18367 (2023). https://doi.org/10.1038/s41598-023-42605-0 (pre-print on Research Square, https://www.researchsquare.com/article/rs-2262084/v1)

  • Yang AHX, Kasabov NK, Cakmak YO. Prediction and Detection of Virtual Reality induced Cybersickness: A Spiking Neural Network Approach Using Spatiotemporal EEG Brain Data and Heart Rate Variability. Brain  Informatics, Springer-Nature (2023) 10:15, https://doi.org/10.1186/s40708-023-00192-w, July 2023. (OA)

  •  J. Lei, J. Li, J. Liu, S. Zhou, Q. Zhang and N. K. Kasabov, "GALFusion: Multi-Exposure Image Fusion via a Global–Local Aggregation Learning Network," in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-15, 2023, Art no. 5011915, https://doi.org/10.1109/TIM.2023.3267525.

  • Wang, X.; Yang, J.; Kasabov, N.K. Integrating Spatial and Temporal Information for Violent Activity Detection from Video Using Deep Spiking Neural Networks. Sensors 2023, 23, 4532, https://doi.org/10.3390/s23094532. (OA)

  • Sensen Song, Zhenhong Jia, Fei Shi, Junnan Wang, Jie Yang, Nikola Kasabov, Saliency optimization fused background feature with frequency domain features, Multimedia Tools and Applications, October 2023, doi: https://doi.org/10.1007/s11042-023-16760-5.

  •  Sugam Budhraja, Maryam Doborjeh , Balkaran Singh, TAN MING XUAN SAMUEL, Zohreh Doborjeh, Edmund Lai, Alexandr Merkin, Jimmy Lee, Wilson Goh, Nikola Kasabov, Filter and Wrapper Stacking Ensemble (FWSE): A Robust Approach for Reliable Biomarker Discovery in High-Dimensional Omics Data" (BIB-23-0262.R2), Briefings in Bioionfrmatics, 2023.    Volume 24, Issue 6, November 2023, bbad382, https://doi.org/10.1093/bib/bbad382 (OA)

  • Zhang X, Liu Y, Wang B, Zhou S, Shi P, Cao B, Zheng Y, Zhang Q, Kirilov Kasabov N. Biomolecule-Driven Two-Factor Authentication Strategy for Access Control of Molecular Devices. ACS Nano. 2023 Sep 26;17(18):18178-18189. https://pubs.acs.org/doi/10.1021/acsnano.3c05070. Epub 2023 Sep 13. PMID: 37703447.

Refereed Conference Publications

2025

  • Doborjeh, M., Doborjeh, Z., Kasabov, N. (2026). Novel Neuron-Stability Weighted Dynamic Evolving Spiking Neural Network (NSW-DeSNN) for Classification of fMRI Data. In: Taniguchi, T., et al. Neural Information Processing. ICONIP 2025. Lecture Notes in Computer Science, vol 16310. Springer, Singapore. https://doi.org/10.1007/978-981-95-4378-6_42

  • Z.Doborjeh, B.Singh, A.Sumich, M.Doborjeh, W. Go, N.Kasabov, Genetic Predictors of Social and Cognitive Outcomes in People with Ultra-High-Risk of Psychosis Using Spiking Neural Networks, Proc. IJCNN 2025, Rome, July 2025

2024

  • Z. Wang, M.Doborjeh, N.Kasabov, The potential of SBNN to predict earthquakes, Proc. ICONIP2024, DOI: https://doi.org/10.24135/ICONIP20, in: M Mahmud, M Doborjeh, N Kasabov, Z Doborjeh (Eds.) Peer-Reviewed Abstracts of the 31st International Conference on Neural Information Processing (ICONIP 2024), 2-6 Dec 2024, Auckland, New Zealand.

  • Mojgan Hafezi Fard, Krassie Petrova, Nikola Kasabov, Grace Y. Wang, The Effect of Prior Programming Knowledge on Memory Efficiency When Learning a New Language, Proc. ICONIP2024, DOI: https://doi.org/10.24135/ICONIP7, in: M Mahmud, M Doborjeh, N Kasabov, Z Doborjeh (Eds.) Peer-Reviewed Abstracts of the 31st International Conference on Neural Information Processing (ICONIP 2024), 2-6 Dec 2024, Auckland, New Zealand.

  • Ravi Kumar Jha, Nikola Kasabov, Damien Coyle, Saugat Bhattacharyya, Girijesh Prasad,  A Hybrid Spiking Neural Network-Quantum Classifier Framework: A Case Study Using EEG Data, 28th Annual Quantum Information Processing Conference, QIP, 2025,  Raleigh, North Caroline, 24-28.02.2025

  • Zohreh Doborjeh, Daniel Lavin, Kirsty Hunter, Nadja Heym, Bryony Heasman, Maryam Doborjeh, Nikola Kasabov, Glen Gibson, and Alexander Sumich, "Neurocomputational Modelling of EEG Connectivity: Links Between Depression, Inflammation, and Gut Microbiome", Proc. Brain Informatics, Springer, 2024.

  • Ravi Kumar Jha, Nikola Kasabov, Damien Coyle, Saugat Bhattacharyya and Girijesh Prasad, Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data, Proc. ICONIP2024, Springer LNCS, 2024.

  • Alexander Sumich, Zohreh Doborjeh, Nadja Heym, Aroha Scott, Kirsty Hunter, Tony Burgess, Julie French, Mustafa Sarkar, Maryam Doborjeh, Nicola Kasabov, Calming the mind: Spiking Neural Networks Reveal How Havening Touch to Reduce Persistent Distress Attenuates Left Temporal Electroencephalographic Connectivity, Proc. ICONIP2024, Springer LNCS, 2024.

  • Sugam Budhraja, Balkaran Singh, Samuel Tan, Maryam Doborjeh, Zohreh Doborjeh, Edmund Lai, Wilson Goh, Nikola Kasabov, NeuroGeMS: An open-source GUI software for multimodal modelling in biomedical research and applications, Proc. ICONIP2024, Springer LNCS, 2024.

  • Balkaran Singh, Sugam Budhraja, Maryam Doborjeh, Zohreh Doborjeh, Edmund Lai, Nikola Kasabov, Izhikevich Neurons in NeuCube for Longitudinal Data Classification, Proc. ICONIP2024, Springer LNCS, 2024.

2023