MRI: Acquisition of High Performance Computing Infrastructure to Support Computational and Data-Enabled Science and Engineering

This project will acquire high-performance data analytic and computing infrastructure to support the University at Buffalo's (UB) new cross-disciplinary PhD program in Computational and Data-Enabled Science and Engineering (CDSE), as well as student/faculty research at the interface of data and computing. Specifically, the proposed resource will enable a broad range of cross-disciplinary research throughout UB, involving 25 affiliated faculty members from across 15 departments. The integration of the resource in the CDSE program is particularly timely given the growing importance that big data, data analytics and simulation based engineering and science (SBES) have on society, science and the economy, as well as the critical need to ensure the development of an adequate workforce with the skills necessary to keep the United States at the forefront of the information age. In particular, the acquired infrastructure will support research and education in a wide range of areas, such as: the development and application of quantum theoretical methods for the simulation of spectroscopic, optical, and magnetic properties of molecular systems; financial market microstructure and asset pricing; machine learning and data mining methodologies for big data; geographic information systems; modeling volcanic eruptions and volcanic ash plumes and ash clouds that rise into the atmosphere; the integration of novel methodologies for large scale computational and data sciences to solve problem ranging from mass flows to biomechanics; regulatory genomics, gene regulation, genome annotation; quantitative network neuroscience; fast and accurate exploration of large biological and engineering data collections; and pharmacokinetic/pharmacodynamics modeling and vertical integration of big-data for target identification. Furthermore, the acquired infrastructure will provide CDSE graduates with computational, mathematical and statistical skills that provide both depth and breadth across the areas of data sciences, applied and numerical mathematics and high performance and data intensive computing. By facilitating the training of these "next generation" data analysts and computational scientists, who will graduate and take jobs throughout the Nation, the project will have an impact far beyond the boundaries of UB in terms of advancing knowledge and understanding across a broad spectrum of fields, including finance, engineering, materials science, geology, medicine, and economics.