[ Research ]
The themes that shape the research: neural signal processing, intelligent systems and their applications in medicine and industry.
Designing EEG-based brain–computer interfaces that translate neural activity into commands — from motor imagery classification and SSVEP frequency recognition to neurorobotics for assisting people with disabilities.
Processing and cleaning electroencephalography (EEG) signals — artifact and noise suppression, time-frequency analysis and coherence estimation using wavelet and synchrosqueezing transforms.
Applying machine learning and deep-learning models to brain-signal classification, health prediction and intelligent systems, including explainable and data-driven approaches.
Digital filter design and performance analysis, image edge detection, segmentation and binarization techniques for real-world signal and image processing problems.