Nikola Kasabov
Papers
18
Total Citations
658
H-Index
10
About
Nikola Kasabov is a pioneering figure in computational intelligence, best known for founding the field of evolving connectionist systems (ECoS). His seminal 2007 book, *Evolving Connectionist Systems: The Knowledge Engineering Approach*, has accumulated over 325 citations and laid the groundwork for adaptive, lifelong-learning neural networks that can grow and restructure in real time. Kasabov’s major contributions span neuro-fuzzy systems, spiking neural networks (SNNs), and neurogenetic modeling, with a particular focus on spatio-temporal brain data. He developed the NeuCube EvoSpike architecture, a 3D SNN environment for pattern recognition of EEG and fMRI signals, which has been widely applied in brain–computer interfaces and rehabilitation robotics. His work on evolving spiking neural networks and neurogenetic systems has garnered over 45 citations, demonstrating its impact on understanding how intelligence emerges from the interplay of genetic rules and lifelong learning. Kasabov has also contributed to practical rehabilitation technologies, including sEMG-based torque estimation and EEG classification for robotic therapy. With over 500 publications and numerous awards, he remains a leading voice in creating brain-inspired, adaptive systems that bridge human and machine intelligence.
Research Focus
Key Achievements
Top Papers
- 1Evolving Connectionist Systems: The Knowledge Engineering Approach325 citations · 2007
- 2Neuro-Fuzzy Techniques for Intelligent Information Systems74 citations · 1999
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- 6sEMG-based torque estimation for robot-assisted lower limb rehabilitation20 citations · 2015
- 7EEG Signal Processing for Brain–Computer Interfaces19 citations · 2013
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