Zin Jun Qiao, a mathematics professor at The University of Texas-Pan American, has received a $500,000 grant from the Department of Defense. Qioa said this is an unclassified research grant from the Department of Defense (DoD). Research topics will focus on Partial Differential Equations (PEDs) and Analysis and Radar Image Reconstruction of Targets. The grant was given to them in January 2008 and it took approximately a year for them to get the grant. They will have this grant for at least three years.

“With this grant, we will be able to develop a way to reconstruct synthetic aperture radar signals,” said Quia. With the analysis and radar imaging project, Qiao said, they will be able to send signals to and from moving targets, such as airplanes.

Qiao said this grant will also be utilized for faculty summer research, Graduate fellowships, scholarships, program materials and supplies.

Their research will help accomplish how a singular structure of the radar data can be extracted quickly and accurately and to develop a way to reconstruct synthetic aperture radar signals.

The research project will be conducted by the university and is composed of three faculty: Professor of mathematics, Zhijun Qiao; Junfei Li, Electrical Engineering professor and another faculty member that is outside the UTPA system.

Students pursuing an engineering degree or mathematics degree will have the opportunity to be part of the research project. Qiao and Li plan to hire up to four students to assist them in their research each semester. Students will also be required to take courses related to the project. Selected students will be able to do research and have the opportunity to work on mathematical modeling, computer simulation and physical measurement in a NSF funded radar laboratory on campus.

Students interested in applying to the DoD program on Micro-local Analysis and Radar Image Reconstruction should be U.S. Citizens or permanent residents, be Electrical Engineering, Mathematics or Computer Engineering majors, have a good standing GPA of at least a 3.0. For more information on the program, contact Professor Zhijun Quiao at 381-3406 or Professor Junfei Li at 316-7148.