Hassibi Research Group

Our research group is a part of the Integrated Circuits and Systems Group (ICSG) of the University of Texas at Austin. Our main strength is in the area of analog and mixed-signal IC design, integrated sensors, and TCAD. However, our current research is more focused on the emerging area of biosensors and bioelectronics with the following 3 major focus areas:

I. CMOS Biosensor System-on-Chip (SoC)

The goal is to design and empirically validate open-platform, silicon-based biosensor ICs which include the transducer, readout circuitry, signal conditioning, ADC, and embedded and digital signal processing (DSP) blocks. The backbone of these systems will be implemented using CMOS processes and, if necessary, modified by post-fabrication steps to accommodate different detection modalities for a variety of applications, ranging form molecular diagnostics to environmental monitoring.

II. Biosensor Modeling and Computer-Aided Design (CAD)

The goal of this thrust area is to develop analytical, mathematical and modeling frameworks to describe and analyze various aspects of biosensor and bioelectronic systems. Recently we have been focusing more on enabling computer-aided design (CAD) and computationally efficient information processing. We believe that the tools and techniques developed in this thrust area, together with the obtained empirical data to be used as feedback, will have significant impact on the design of biosensor-related ICs, transducers, and molecular interfaces, and on the understanding of their interplay.

III. High-Perfomance Biochemical “Circuit” Design

The physicochemical component (assay) of biosensor systems include complex biological and multi-analyte biochemical processes which can be described as a biochemical “circuits”. In this thrust area of our research, we plan to study, model, and exploit the unique characteristics of these networks to design and empirically validate high-performance biochemical “circuits” with the ultimate goal of enhancing the SNR, dynamic range (DR), and response time of biosensor systems.