As a researcher, my primary goals are to improve existing techniques and invent new paradigms that will hopefully inspire other researchers. My primary research areas are sparse representation, compressive sensing, wavelet analysis, as well as signal, image and video processing. In addition, my current interests and on-going research topics include, but are not limited to:
(1) Signal separation poblems. I study various methods to perform signal separation from one observatiion as well as multiple observations.
(2) Compressive sensing and sparse representation. I study sensitivity analysis of dictionary perturbation on the compressive sensing framework. I also study the sparse representation structure under the frame representation.
(3) Integration of fundamental image processing problems. I study using the deep structure based on graph trying to bring all togher many fundamental image processing problems such as denoising, deblurring, segmentation, and classification.
(4) Wavelet analysis and time-frequency analysis: Having studied wavelets for many years since obtaining my Ph.D., I am interested in several advanced wavelet techniques – both theoretical and practical. I have co-authored a book on time-frequency analysis, and I am currently using time-frequency methods to process oscillatory signals.
(5) Adaptive signal processing and learning based on operator approach.
In summary, I like to study and develop new methods because I derive immense satisfaction from solving complex problems.