I-Corps: Intelligent visual framework for analyzing chemical measurement data

Texas Tech University, Lubbock TX

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is to explore substantive enhancements for the end-users of field-portable sensors. This project proposes an intelligent visual framework for analyzing chemical measurement data. The proposed solution also recommends personalized visualizations through the user’s preferences and interactions. This system can be used for applications in the biological domain and high-performance computing centers. This I-Corps project explores translation of a system that provides and recommends a full range of visualizations from one-dimensional (1D), two-dimensional (2D), three-dimensional (3D), to higher-dimensional (nD) data. Application domains that generate multivariate data can also use our technology. For example, in the biological domain, the framework can help detect and present the dependency network of genes based on their experimental mutation data. Other applications include automatically detection of the links between various health metrics in supercomputing centers (such as CPU temperature, memory usage, and power consumption), which are growing in terms of size and complexity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.