Nicolai Petkov's initial research in the 1980s and early 1990s was in the field of systolic parallel algorithms. After that he worked mainly on brain-inspired computing. In this area he considers as most valuable his and his students' work on the computational modeling of non-classical receptive field inhibition (also known as surround suppression) in neural cells in the visual cortex. This pioneering work provided explanation of various visual perception effects, such as the masking effect of texture on the perception of object contours and the orientation-contrast pop-out. It led to the development of more effective computer vision algorithms for various industrial, medical and other applications. His further work was/is for the development of pattern recognition and machine learning algorithms for various types of data: image, video, audio, and time series with applications in robotics, manufacturing, agricultural industry, medicine, finance, etc.