Daniel George

 Daniel George

Contact Information

Department of Astronomy
133 Astronomy
1002 West Green St.
Urbana, IL
MC 221
PhD Candidate
View CV - Visit Website


Daniel is a PhD candidate in Astronomy and a Computational Science and Engineering Fellow at the University of Illinois at Urbana-Champaign. He obtained his Bachelor's degree in Engineering Physics from IIT Bombay. He is a Research Assistant in the Gravity Group at the National Center for Supercomputing Applications (NCSA), working with Profs. Gabrielle Allen, Eliu Huerta, Zhizhen Zhao, and Ed Seidel. He is also a member of the LIGO, NANOGrav, and Dark Energy Survey collaborations, and an LSST Data Science Fellow. He has previously interned at Los Alamos National Lab and worked on deep learning and natural language understanding at Wolfram Research (Mathematica, WolframAlpha). He is currently a Machine Learning and AI Resident at Google X. He recently won the ACM Student Research Competition and also the NVIDIA Graduate Fellowship.

Research Interests

  • Gravitational Wave and Multimessenger Astrophysics
  • Machine Learning, Deep Learning
  • Signal Processing, Data Science
  • High Performance Computing, Numerical Relativity
  • Natural Language Processing, Artificial Intelligence

Research Description

Daniel’s research is at the interface of deep learning, high-performance computing, and gravitational wave astrophysics. He employs massively parallel physics simulations on petascale supercomputers including Blue Waters for generating data to train artificial intelligence algorithms that he is developing for time-series signal processing, using deep neural networks which can exploit emerging hardware architectures such as deep-learning-optimized GPUs, to enable real-time analysis of highly noisy big data from the LIGO detectors and telescopes such as LSST, to push the frontiers of multimessenger astrophysics. His long-term interests lie in applying cutting-edge computer science and technology, especially artificial intelligence, to accelerate discoveries in the fundamental sciences.

Research group webpage: http://gravity.ncsa.illinois.edu/

CV: https://illinois.academia.edu/dan7geo/CurriculumVitae


  • IIT Bombay - Bachelor of Technology in Engineering Physics (with Honors) - 2015
  • University of Illinois at Urbana-Champaign - Master of Science in Astronomy - 2017

Distinctions / Awards

Selected Publications

Journal Articles

George, Daniel, and E. A. Huerta Deep Learning for real-time gravitational wave detection and parameter estimation: Results with Advanced LIGO data Physics Letters B 2018. DOI.
George, Daniel, and E. A. Huerta Deep neural networks to enable real-time multimessenger astrophysics Physical Review D 97 044039 2018. arXiv. DOI.
George, Daniel, Hongyu Shen, and E. A. Huerta Classification and clustering of anomalies in LIGO with Deep Transfer Learning Physical Review D - Rapid Communications 2018. DOI.

Website Articles

George, Daniel, Hongyu Shen, and E. A. Huerta Glitch Classification and Clustering for LIGO with Deep Transfer Learning NIPS 2017, Deep Learning for Physical Sciences 2017.
George, Daniel, and E. A. Huerta Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation with Real LIGO Data NIPS 2017, Deep Learning for Physical Sciences 2017. URL.

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