Past Awardee

Deep Learning to the Rescue: Enabling the Search and Characterization of New Classes of Gravitational Wave Sources with Novel Applications of Machine Learning

Zhizhen Zhao
Zhizhen Zhao

College: Grainger College of Engineering
Award year: 2017-2018

Recent detections of gravitational waves (GW) by LIGO opened a new era of astronomy. Extracting weak GWs, which are buried in the background noise, and rapidly inferring the physical parameters of the source are crucial in enabling the scenario of multi-messenger astrophysics. Current data analysis pipelines are limited by high computational costs. We propose to develop a unified and highly efficient computational framework to process the data. The application of new deep learning techniques in GW astrophysics, astronomy, and astroparticle physics has the potential to accelerate scientific research and unlock new opportunities by enhancing the way we use HPC resources and exploit emerging hardware architectures such as DL-optimized GPUs.