Research >> Modelling & Simulation >> Signal and Data Science

Signal and Data Science

Following are the topical problems of interest under the broad category of multiscale modeling and simulation arising from spatial-temporal signal processing, imaging and the associated problem of data representation, data compression and model-order reduction. Most of these methods are actually quite well established methods used for material structure-property correlation. However, the problem of micro/nano-material structure-property correlation calls for greater insight to the signal characteristics and measured data. Similarly, in composite materials with inhomogeneous phases, material structure-property correlation requires identification and separation of certain signals and measured data sets. Several of these problems lead to non-linear and discrete optimization problems. Below is a list of problems we are studying.

Ultrasonic guided wave propagation and scattering
Laser-ultrasonics
Multifunctional imaging with spectroscopy
RF and microwave signal propagation and wireless sensing
Electromagnetic wave scattering and absorption by nanostructures
Optoelectronic signal processing in bio-systems diagnostics
Statistical machine learning from spatio-temporal signals involving ultrasonics, optical/photonic sensing/imaging