Physics & Engineering Physics Colloquium

Viviana Acquaviva, Ph.D., professor in the physics department at the CUNY NYC College of Technology and at the CUNY Graduate Center, will present “Understanding the Universe Using Machine Learning.”

Astronomy has truly become a “Big Data” science in the last few decades thanks to technological advances in telescopes development and the availability of space-based observations. Machine learning techniques are found to be increasingly useful in solving a variety of problems, from the automatic classification of galaxy morphology and source identification in crowded fields to estimation of star and galaxy properties, outlier recognition and anomaly detection, and dimensionality reduction, just to quote a few examples. In this talk, Acquaviva will review some of the most notable applications of machine learning and deep learning to the analysis of astronomical data and present a few specific examples drawn from her research experience in analyzing galaxy spectra and training models on cosmological simulations.