We synthesize, extend, and apply theoretical breakthroughs on Machine Learning, Compressed Sensing, and Sparse Representations, to emerging Imaging applications. Our key areas of interest range from Active Range Imaging, to Land-cover classification for remote sensing, and Computational Photography.
We have a distinct focus on signal acquisition/representation, distributed processing, and context retrieval from heterogeneous sensing devices, as well as on autonomic networking algorithms for limited bandwidth, limited power, and limited capacity wireless sensors, which serve the design paradigm of IoT and CPS.
We perform cutting edge research, featuring microphone array signal processing, wireless acoustic sensor networks, multichannel audio coding, immersive audio capturing and reproduction, sound source separation, speech enhancement for improved intelligibility, and robust automatic speech recognition.