Our lab’s focus is where information and learning theory meet the physical world. This involves developing efficient algorithmic structures to address emerging problems of fundamental interest involving the manipulation of signals and information in diverse physical settings, with an emphasis on system intelligence. The lab’s research ranges from the development of fundamental limits and architectural principles, to implementation issues and experimental investigations. Of particular attention in recent years have been problems of information representation, extraction, distribution, and security arising in the context of statistical inference, machine learning, and artificial intelligence; computational imaging and sensing, computer and machine vision; architectures for nanoscale to network-scale systems and technologies for computation, storage, sensing, and perception; computational neuroscience, brain-machine interfaces, and bioengineering; and wireless networks.
