Deformable image registration is fundamental and critical to both diagnostics and therapeutics in precision and personalized medicine. Existing software packages for deformable registrations either provide only a forward deformation vector field (DVF), or render both forward and backward DVFs with time-intensive computation. The latter has multiple advantages in medical image analysis and processing. However, its latency, which is substantially longer than clinical time windows, hinders the transition of its benefits to clinical applications.

The emergence of Data Science has led to a flourishing of initiatives, centers, degrees, programs and organizational units at educational and research institutions around the world.  The demand for data science know-how from students, parents, scientists and employers is strong and getting stronger.  However, the interdisciplinary nature of the topic and the lack of a consensus around its definition raise challenges for its implementation in the modern university setting.

inDuke TechConnect, an event hosted by the Duke University Department of Computer Science,  Pratt School of Engineering,  and Career Center,  brings students and employers together for networking and education.