SSEI trainees will receive a Ph.D. through existing programs in Chemistry, Chemical Engineering, Electrical and Computer Engineering, Physics, or Spatial Information Science and Engineering. All SSEI IGERT trainees will complete a two-year, 15 credit Certificate in Sensor Science, Engineering and Informatics.
SSEI IGERT trainees will receive interdisciplinary mentoring from participating IGERT faculty. Each fellow will have a thesis topic in the area of sensors and will have a primary mentor from his or her home department and another advisor from a complimentary research area. The dual mentoring system will facilitate participation by trainees in at least one major interdisciplinary research project that reflects connections across the focus areas and forms the basis of a dissertation.
The SSEI program focuses on the following areas of sensor research:
Sensor Materials and Devices
Sensors and sensor arrays are critical components for diverse applications such as environmental monitoring, chem-bio defense, biotechnology and medical diagnostics, food quality monitoring, and industrial process control. A critical need exists to optimize sensing materials, especially their surfaces, to achieve high sensitivity, selectivity, and reliability. Research activities in this area include thin film materials development, surface chemistry, biochemistry, nanobiotechnology, the study of transduction mechanisms, development of sensing platforms, device fabrication and packaging, and testing of prototype sensor systems.
Sensor Systems and Networks
Sensor systems incorporate sensors and actuators together in order to perform a measurement and/or control function. Current research projects in this area encompass a wide variety of measurement instruments for medical, biological and chemical analysis applications, all of which are realized using silicon microsystems technology including micromachining and nanofabrication, and associated materials processing and characterization. The aim is to produce data streams with low noise and standardized outputs that are compatible with that from other sensors, and with off the shelf electronics. Specific research areas are signal conditioning for noise immunity, detection and generation of small signals in the presence of noise, and characterization and compensation of nonlinearities introduced by the sensors.
Large arrays of sensors and expanding sensor networks incorporating many different sensor types with different sensing regimes (in space and time) contribute to a rapidly growing pool of heterogeneous data. Creating useful information from this pool both for feedback to adaptive sensor systems themselves and to humans engaged in various decision-making tasks requires new modeling, management and analysis strategies. Research in this area covers modeling and management strategies for sensor data streams, data mining and event detection in data streams, context based reaction and reasoning based on sensor information, and protection of personal information privacy in sensor environments.