Prof. Clay Scott, assistant
professor in the division of Electrical and Computer Engineering, was
recently awarded an NSF CAREER grant for his research project, "Guided
Sensing," which offers a unique approach to the problem of mining the vast
stores of information available for any given problem. Scott's specific
interest is to develop and apply new theory for biomedical applications.
To describe the project in general terms, in many complex problems
related to discovery, detection, and diagnosis, researchers and
practitioners alike are continually faced with the question “What data
should I gather next?” When the possibilities for data collection are
overwhelming, and experiments or measurements are costly or time-consuming,
this question becomes all the more critical.
This research investigates guided sensing algorithms, which make
recommendations about the next measurements to gather, with the
understanding that a domain expert makes the final decision. This work
develops new methods for guided sensing that account for temporal and
task-based constraints, missing data, and environmental noise as well as
More specifically, the proposed work is strongly connected to two
motivating applications: (1) Rapid identification of toxic chemicals in
emergency response situations; and (2) Design of flow cytometry experiments
for analyzing cell-based diseases. Through collaborations with experts in
each field, the methods developed will be disseminated to actual users and
implemented in real systems.
The proposed work has the potential to impact potentially thousands or
even millions of citizens who are victims of toxic chemical accidents or
bioterrorism, or who suffer from hematological disorders such as lymphoma
and leukemia. Furthermore, the proposed work will apply more broadly to
other problems where rapid identification or sensor scheduling are critical,
such as machine fault monitoring and remote sensing.
The educational component of this CAREER award is aimed at improving the
motivation of college students taking their first course in Probability, a
theoretical course that is required for electrical engineers. Prof. Scott
teaches this course, and intends to peak students' interest by relating the
material to real-world problems through the introduction of three specific
examples that will illustrate the theory being taught. Probability is often
a student's first exposure to the kind of abstract, mathematical thinking
that characterizes advanced study in Signal Processing, Communication, and
Clay Scott's research interests include machine learning, pattern
recognition, data mining, statistical learning theory, and statistical
signal processing. He is particularly interested in the application of his
research to real-world problems, especially in the biomedical field.
The CAREER grant is one of NSF's most prestigious awards, conferred for
"the early career-development activities of those teacher-scholars who most
effectively integrate research and education within the context of the
mission of their organization."
Posted: December 16, 2009 by
EECS/ECE Communications Coordinator
email@example.com or 734-936-2965
Related Topics: Big Data Medical diagnosis Scott, Clayton D. Security (National, and Personal Safety) Signal and Image Processing