RF-Based Analytics with Intelligent Backscattering in Passive Tag-to-Tag Networks
We propose tiny RF tags that power themselves by harvesting available RF power and that can communicate with each other, collaborate, and sense the environment through a novel concept of wireless channel estimation with passive backscattering tags. The tags form a collaborative, distributed sensing network that can “see” and “recognize” changes, activities, and interactions in the ambient environment. (supported by NSF CISE)

Passive Network of Tags for Smart Spaces
We develop RF tags intended to provide ‘last-link’ connectivity to all types of objects making the IoT a vastly more inclusive paradigm. The main research goal is targeted towards establishing connectivity between objects with tag-to-tag communication, enabling the large network with multihop routing and determining inter-object dynamics by intelligent backscattering between two tags. (supported by NSF CISE)

Breath-Based Early and Fast Detection of COVID-19 Infection
The goal of the project is design of a handheld breath analyzer for gas detection in exhaled human breath that rapidly and selectively identifies the presence and monitors the concentration of trace levels of specific gaseous analytes-biomarkers. The concentration level of specific biomarkers in exhaled breath can be used for rapid detection of COVID-19 infection. (supported by NSF EAGER)

Charge-Recycling based Computing Paradigm for Wirelessly Powered Internet-of-Things,
The goal of the project is enhancing the computational capabilities of the wirelessly power devices by introducing the new concept of AC computing. Instead of converting AC signal to DC to sup- ply voltage to digital circuits, we leverage the existing charge-recycling theory and adapt the digital logic to operate with the harvested AC signal as power-clock signal. (supported by NSF CISE)
Acoustic localization and separation
The objective of this research is design of algorithms and real-time system implementations for task of source localization and separation using miniature sensor arrays, where dimensions of the arrays are much smaller than wavelength of the incident signals. The approach is the integration of wavefront sensing and independent component analysis in unique framework that extends the performance of current source separation algorithms and lends itself into efficient implementation in mixed-signal VLSI, yielding real-time performance at small-form factor. (supported by NSF CAREER award)

Smart Radiation Detection Readout IC
Significant efforts have been made recently to enhance the effectiveness of nuclear and radiological detection capabilities, specifically in design of portable systems that would be able to localize the threat. A proposed three-dimensional (3D) integration of scintillation-type semiconductor detector pixels provides accurate spectroscopic resolution for isotope discrimination and an accurate determination of the direction to source at the same time. We are investigating the design of integrated readout circuitry for measurement of the optical response of pixelated detector. (supported by Department of Homeland Security)

RF ID pill
Drug uptake by patients often needs to be tracked, especially in psychiatric patients, transplant patients and elderly people. The objective of this research is design of an integrated system that would be inserted in a pill and enable monitoring of ingestion of medicine and absorption into the body to insure proper dosage control and usage. (supported by School of Medicine, Stony Brook University)