Our research currently resides at the intersection of optics/materials, nonlinear dynamics, and data science.  Our investigations involve both experiments and computation.  In many of the systems that we study, the noisy statistics that would normally be filtered out become the signal to be studied.

Specific interests currently: computer vision-related coded diffraction applications; liquids with multiple phases (metal-nanoparticle dispersions, conducting-polymer latices, and ionic liquids), and systems with "structure" (vorticial flows, light with angular momentum, chiral asymmetric modes, fractal images, porous media). We analyze large data sets from multiple modes of measurements with an emphasis on spectral methods, physics-informed data preprocessing (analog or digital) and experimental design, which reduces the computational complexity of any data postprocessing. 

What determines the growth or structure of a nanocomposite material? How can we predict and control the patterns and energy and optical flows that emerge within? How do we infer information, underlying physical or chemical phenomena from measurements of complex dynamics? The answers to these questions aid the design and development of next-generation light and heat-harvesting systems, optoelectronic materials, and adaptive imaging and sensing algorithms.  

Contact: LuatV@UCR.edu (PI)