Zamese Peters

Zamese Peters

PI: Fernanda Eliott, PhD , Department of Electrical Engineering

Is is possible to embed an Astronomy common sense into an Artificial Intelligence system in order to create meaningful scatterplots

Data mining is the act of turning raw data from an observation into useful information. This information can be interpreted by hypothesis or theory, and used to make further predictions. Astronomers receive huge datasets filled with petabytes of information and working through all of this data to find patterns and relevant trends would be extremely difficult. The Artificial Intelligence Visual Analogical System lab is creating an artificial intelligence system to aid in this mission. I am working on creating a catalog of different attributes, which are the values in the data fields describing the properties of each object. This will be created for various star and galaxy classes which will contain attributes such as mass, radius, bolometric magnitude, effective temperature, velocity, velocity dispersion, luminosity, multiwavelength data, and many more. We expect that our work will aid astronomers in creating new mechanisms by which to measure intrinsic properties of stars and galaxies.