Keenan Crane, an assistant professor in the Computer Science Department and Robotics Institute, has been awarded a four-year, $519,000 Faculty Early Career Development (CAREER) Award, the National Science Foundation's most prestigious award for young faculty members.

The award will sponsor his development of methods that allow software users to take advantage of the rapidly growing volume of 3D geometric data. This fundamental work promises to enable a wide variety of applications, such as searching large databases to find 3D shapes, predicting whether a shape will stand up or fall down when created in a 3D printer, and more reliably detecting anomalies in CT or MRI scans.

Technologies for acquiring digital 3D data, medical imaging and digital manufacturing are creating a glut of 3D data, Crane said. But this data is often underutilized in science, engineering and medicine because it is structured in ways that "break" algorithms. So Crane has proposed developing an interface between bad 3D data and good algorithms — a black box that will help both expert and nonexpert users to ignore the problems related to data structure and focus instead on applications goals.

Crane notes that the project harkens back to radical mathematical ideas of the 19^th century.

"Basically, mathematicians realized that you could think about shape not from a human perspective, but from the perspective of a small bug crawling around a surface," he explained. This "intrinsic" point of view, which Crane will explore with his NSF support, hasn't really been taken all the way to its natural conclusion when it comes to computational/algorithmic problems, he added.

Crane joined the CMU faculty in 2015. He earned a Ph.D. in computer science at Caltech and previously completed an NSF Mathematical Sciences Post-Doctoral Fellowship in Columbia University's Department of Computer Science.