rapid methods of MR Imaging fusion of Electrophysiology and fMRI advanced approaches to MR data analysis ultra-low field MRI using SQUID detection low energy focused ultrasound for neurostimulation the science of images: representation, information, resolution Mark Cohen’s training is equal parts engineering and neuroscience. His contributions include his critical role in the development of practical echo-planar scanning, ultra-fast MRI applications, contrast-based and BOLD functional MRI, applications of linear systems analysis to increase fMRI sensitiivity and resolution, and concurrent recordings of EEG and fMRI to better understand brain dynamics and distributed processing. He and his lab have contributed to an understanding of the power of pattern recognition and machine learning to both interpet/classify neural data and as a source of discovery of the processes that result in cognition, perception, emotion and pathology. Cohen is passionate about graduate and post-graduate education. As the creator and director of the UCLA/Semel NeuroImaging Training Program he has pushed his students to an integrative understanding of the role of imaging in neuroscience: The use of images as hypothesis tests, the relationship between blurring, convolution, statistical error and inference from images, and an understanding of the structures common to neuroimages regardless of imaging modality. His current focus now includes inquiry into the broader problems of images, beyond neuroscience, to encompass astronomy and nanoscale imaging, aesthetics to statistics, dimensional compression and dimensional expansion.