The University at Buffalo, N.Y., has received a $2.9 million National Science Foundation grant to transform the traditional role of a database as a repository for information into an automated computer laboratory that rapidly collects, interprets, and learns from massive amounts of information.
The lab, which also will conduct large-scale materials modeling and simulations based upon untapped troves of visual data, will be accessible to the scientific community and ultimately speed up and reduce the cost of discovering, manufacturing and commercializing new materials.
“This pioneering and multidisciplinary approach to advanced materials research will provide the scientific community with tools it needs to accelerate the pace of discovery, leading to greater economic security and a wide range of societal benefits,” said Venu Govindaraju, PhD, UB’s vice president for research and economic development.
Dr. Govindaraju, SUNY Distinguished Professor of Computer Science and Engineering, is the grant’s principal investigator. Co-principal investigators, all from UB, are: Krishna Rajan, ScD, Erich Bloch Endowed Chair of the Department of Materials Design and Innovation (MDI); Thomas Furlani, PhD, director of the Center for Computational Research; Srirangaraj “Ranga” Setlur, principal research scientist; and Scott Broderick, PhD, research assistant professor in MDI.
The award, from NSF’s Data Infrastructure Building Blocks (DIBBS) program, draws upon UB’s expertise in artificial intelligence, specifically its groundbreaking work that began in the 1980s to enable machines to read human handwriting. The work has saved postal organizations billions of dollars in the U.S. and worldwide.
UB will use the DIBBS grant to create what it is calling the Materials Data Engineering Laboratory at UB (MaDE @UB). The lab will introduce the tools of machine intelligence — such as machine learning, pattern recognition, materials informatics and modeling, high-performance computing and other cutting-edge technologies — to transform data libraries into a laboratory that not only stores and searches for information, but also predicts and processes information to discover advanced materials.
