Stony Brook Milutin Stanacevic
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)
Integrated electronics for biomedical applications
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)

Gas and bio-metabolite detection: The detection and monitoring of gases in exhaled human breath to-date has been limited by the lack of appropriate materials and technologies which could rapidly and selectively identify the presence and monitor the concentration of trace levels of specific analytes, biomarkers. Conventional techniques lack the relative specificity to a mixture of gaseous analytes for these sensing elements, requiring the use of pattern recognition algorithms to process the signals and match the acquired data profile to a known pattern, thus identifying the signature of the odor or gas detected. We are investigating the design of selective sensor arrays systems for discrimination and monitoring of bio-chemical metabolites that signal diseases.