Signal Processing and Information Systems Lab
We are interested in research, education, and engineering applications of signal and image processing. Our research is focused around the general theme of developing statistically-based methods for robust and efficient information extraction from observed uncertain, limited data. Our current research spans a wide variety of topics including (1) inverse problems and computed imaging with applications to radar, biomedical imaging, nondestructive evaluation, and array processing; (2) sparse signal representation and compressed sensing; (3) signal and pattern analysis, with distinct research thrusts in image segmentation, EEG-based brain-computer interfaces, and facial expression analysis based on video data; (4) data fusion, distributed inference, and sensor networks with a focus on communication-constrained inference and with applications to multi-sensor multi-target tracking and random field estimation.
Our laboratory provides an extremely interactive research environment for faculty, post-doctoral researchers, as well as both graduate and undergraduate students. Our laboratory is closely affiliated with the Computer Vision and Pattern Analysis (VPA) Laboratory, and holds strong collaborations with a number of groups around the world.