Advances in Signal Processing, Information Theory, Machine Learning, and Statistical Computing have significantly impacted virtually all aspects of scientific data analysis and information technology. A major and fundamental issue we face today is how to constructively and efficiently analyze and process a profusion of measured signals and information. Medical and biological measurement systems, the Internet and wireless communication networks, and remote sensing and imaging systems provide us with information-bearing signals from a myriad of sources and sensors that must be transmitted, fused, stored, analyzed and interpreted effectively and in a computationally tractable manner. In short, we face a challenging and vital task -- analyzing and processing more data and information than ever before. Research activities in our group address this challenge by focusing on issues related to theory, algorithms, and applications in signal and image processing, pattern recognition, biomedical data analysis, networking, and wireless communications.