Jie Shi selected to attend the 2012 Summer School on Geometry and Data

Jie Shi, doctoral student in computer science, has been admitted to the 2012 Summer School on Geometry and Data. The CGAD Summer School program brings students to the leading edge of research at the intersection of geometric measure theory and geometric analysis with data analysis and inference from noisy data.

Shi works in Yalin Wang’s lab in the School of Computing, Informatics, and Decision Systems Engineering.

In the lab, Wang, students and visiting professors apply modern geometry knowledge to solve practical computer vision and medical imaging problem. They are developing unique medical imaging technology that enables 3-D mapping of the brain. The technology can be used to better diagnose and treat disease as well as analyze drug efficacy.

Wang, an assistant professor, stresses the opportunities for students in the lab through programs like this as well as conferences and publications.

“Much work goes in to the data collection, analysis and reporting of this research. Students in the lab have excellent opportunities to publish and present their work,” he says.

Students also gain hands-on experience in the field. Wang collaborates with Banner Alzheimer’s Institute, Barrow Neurological Institute and Mayo Clinic, working on 3-D imaging to better diagnose and treat diseases like Alzheimer’s disease. Other collaboration includes projects with the Biodesign Institute at ASU, the Los Angeles Children’s Hospital and The Ohio State University.

“The summer school program will give Jie an opportunity to gain a broad view of the opportunities in this field. Plus, she will have the opportunity to meet with top researchers in applied mathematics. The experience directly relates to our work, and gives her an opportunity to consider topics for her doctoral proposal and defense,” says Wang.

Seventeen faculty members from across the country will present insights from about 20 papers.

The program is sponsored by the Center for Geometric Analysis and Data with support from the U.S. Department of Energy, National Science Foundation, Washington State University and University of Idaho.