The intersection of signal processing/machine learning, computer science, material engineering and neuroscience is beginning to open up exciting opportunities for important advances in systems and cognitive neuroscience and in translational neuroengineering. Our work over the past 15 years has focused on taking advantages of these opportunities. Our neuroscience research investigates the neural basis of motor, language, and cognitive function by applying computational techniques to recordings from the surface of the brain (electrocorticography (ECoG)) in humans. For example, we study how local field potentials in different cortical areas prepare for and execute hand or finger movements. Our neuroengineering research is taking advantage of the resulting neuroscientific understanding and aims to address particular clinical problems. This work includes statistical signal processing, machine learning, and real-time system design and implementation. For example, we have been developing a new real-time imaging technique for invasive brain surgery. In this talk, I will describe the types of signals that can be detected in ECoG and the emerging understanding of their physiological origin. I will then demonstrate that ECoG encodes detailed aspects of function, such as actual or imagined speech. Finally, I will show demonstrations of ECoG-based communication and control, and of our real-time passive functional mapping technique. Overall, this talk aims to communicate the substantial research and emerging commercial opportunities that arise from integration of neuroscience and neuroengineering, and hopes to inspire the neurotechnology community to participate in them.