My work develops new sensing/imaging modalities that rely on a carefully optimized capture process yielding computationally encoded measurements from which the information is decoded using recovery algorithms. This is fundamentally different from the traditional approach where hardware and algorithms are treated as decoupled entities.
The purpose of my research is to achieve a synergistic balance between hardware and algorithms by means of a co-design, so that popularly held limits in data capture and imaging can be broken. My work relies on a true melding of hardware and algorithms that is grounded in a scientifically principled approach.
My long-standing goal is to catalyze revolutionary methods for data sensing and imaging with emphasis on health diagnosis and consumer applications. To achieve this, I build on the theoretical foundations of mathematics; harmonic analysis, inverse problems, signal processing and high dimensional statistics.
Through multi-disciplinary and multi-institutional collaborations, my work creates tangible impact on real-world applications and poses new theoretical problems.