With a key goal to integrate research and education by advancing discovery and understanding while at the same time promoting teaching, training, and learning at both the undergraduate and graduate levels, the Tufts Center for Scientific Visualization includes a high-resolution display wall, with far more pixels than conventional computer desktop displays, and far higher than conventional home “High Definition” TV displays. Rear screen projection is used, allowing the viewers to approach the screen for detailed analysis without blocking the projected image. Stereoscopic vision is included, involving special glasses that separate the left-eye image from the right-eye image.
An in-room computer provides the signal source for the images, and allows the viewer to “steer” the results during the viewing experience. A custom-built solid aluminum frame simultaneously holds the projector/screen combination so that the units are permanently aligned to each other without being dependent on the structure of the room itself.
Because the Facility is integrated with Tufts University’s Access Grid node, it allows Tufts researchers to combine visualization and teleconferencing with colleagues throughout the world.
National Science Foundation funding for this project was awarded in August 2006 to Tufts University via Principal Investigator Bruce Boghosian, Professor and Chair of the Department of Mathematics, and co-PI’s Robert Jacob, Professor of Computer Science, and Mely Tynan, Chief Information Officer and Vice President of Information Technology at Tufts. The School of Engineering, the School of Arts & Sciences, and University Information Technology (UIT) collaborated together to provide funding for the construction and remodeling of the space that houses the Visualization Wall.
The Center for Scientific visualization was inaugurated on February 8, 2008.
While other research universities have created Visualization Facilities, this is the first such Facility at Tufts. Seed projects for early use have included fluid dynamics, geotechnical engineering, human factors in medical systems, image reconstruction and tomography, computational geometry, robotics, chemical mechanical planarization, computational anatomy and visualization itself.