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Justin Sirignano

University of Illinois at Urbana-Champaign


IE 498: Deep Learning

Jan 2020 - May 2020

Deep Learning

Sep 2019 - Dec 2019

Deep Learning

Feb 2019 - May 2019

Deep Learning

Sep 2018 - Dec 2018

Deep Learning II

Jan 2018 - Apr 2018

IE 598: Deep Learning (Fall 2017)

Sep 2017 - Dec 2017

Deep Learning

Sep 2017 - Dec 2017

Deep Learning with GPUs

Apr 2016 - Dec 2016


Justin Sirignano, Jonathan F. MacArt, and Jonathan B. Freund (2020): DPM: A deep learning PDE augmentation method with application to large-eddy simulation, Journal of Computational Physics, Elsevier Inc., Vol 423, pp109811


Justin Sirignano and Rama Cont (2019): Universal Features of Price Formation in Financial Markets: Perspectives from Deep Learning, Quantitative Finance, Routledge, Vol 19, Num 9, pp1449-1459


Justin Sirignano and Konstantinos Spiliopoulos (2018): DGM: A Deep Learning Algorithm for Solving Partial Differential Equations, Journal of Computational Physics, Elsevier BV, Vol 375, pp1339-1364


Jonathan Freund, Justin Sirignano, Jonathan MacArt (2019): Machine-Learning Turbulence Models for Simulations of Turbulent Combustion, 2019 Blue Waters Annual Report, pp148-149
Justin Sirignano, Jonathan B. Freund, Jonathan F. MacArt (2019): HPC Development of Deep Learning Models in Scientific Computing and Finance, 2019 Blue Waters Annual Report, pp234


Justin Sirignano (2018): Topology-Aware Distributed Graph Processing for Tightly Coupled Clusters, 2018 Blue Waters Annual Report, pp187

Blue Waters Illinois allocations awarded to 26 research teams

Mar 7, 2017

Twenty-six research teams at the University of Illinois at Urbana-Champaign have been allocated computation time on the National Center for Supercomputing Application's (NCSA) sustained-petascale Blue Waters supercomputer after applying in Fall 2016. These allocations range from 25,000 to 600,000 node-hours of compute time over a time span of either six months or one year. The research pursuits of these teams are incredibly diverse, ranging anywhere from physics to political science.