Synergy of Diverse Parts

Venn Diagram

The Bioelectronics Laboratory research interests include bioelectronics and optimization methods for physical circuit design, low-voltage and biologically inspired computing, sensor-processor integration, and wireless networking and communications. Current research focuses on developing sense-and-respond systems for blood metabolites and vital signs as well as volatile organic compounds/gas detection in trauma patients and crowded areas.

With the advancement of sensor and circuit design, sensing systems as a viable technology alternative are growing at a very rapid pace, which allows us to develop methodology, models, and algorithms to handle applications ranging from biomedical sensing to environmental monitoring. Our computing systems require cost-effective miniaturized sensors with the appropriate sensing element, data processing and storage, off-chip communication, and a power management module all interconnected within a full-bodied package and exhibit lifetimes on the order of years. Due to the power limitations of sensor systems, that is high power consumption reduces the ability to design long-lasting sensor system and limits the performance of the system. Thereby, to increase the lifetime requirement of sensor systems, we must minimize the power consumption of all system components by aggressively scaling supply voltages in such applications to maximize energy efficiency through the exploration of low voltage systems design and test to meet the stringent energy budgets.

The objective of our research is to improve sensor system design productivity by applying statistical models to compute the statistical performance of our sensor system, and using stochastic optimization to optimize the statistical performance. We continue to explore the mitigation of process variability at low voltage and demonstrate the energy benefits of low voltage operation using 8-bit processor and SRAM for low voltage systems. Our studies of low voltage operation using processor and memory are making important strides toward viable sensing systems by integrating our sensor systems with a DC-DC converter and inertial power systems.

The cross-disciplinary education activities aim at two aspects of computer engineering education: 1) educating students in formal methods, especially their applications to nanometer biosensor system design, thus bringing needed nanobiotechnology and mathematical rigor into the discipline and 2) introducing students to microfabrication and microelectromechanical systems (MEMS) complexity and their impact on biosensor system design so that they are equipped with necessary background for modern high performance sensor design.

Department of Computer Science and Electrical Engineering
University of Maryland Baltimore County