The long-term goal of Dr. Suzuki’s research is to develop and understand computational intelligence that learns, from data and examples, experts’ knowledge and skills in understanding images in order to make smart decisions. To approach his goal, he believes that the development of sophisticated machine-learning and image-analysis techniques, their theoretical backups, and an understanding of experts’ decision-making process and of the human visual system are essential. Areas of his interest include machine/data learning in biomedical imaging, computer-aided detection and diagnosis of lesions in biomedical images, and biomedical image processing and analysis, especially machine learning inspired by the human visual system for image processing and pattern recognition such as image-based machine learning and deep learning, and its applications in biomedicine.