Science at Extreme Scales: Where Big Data Meets Large-Scale Computing

September 12 - December 14, 2018

Seminar Series

No schedule is available

Thursday, October 4, 2018

Afternoon Session

14:00-14:30

Erin Molloy (University of Maryland)

Scaling species tree estimation methods to large datasets using NJMerge

14:30-15:00

Philipp Haehnel (Dana-Farber Cancer Institute)

Scaling up Deep Learning for PDE-based Models

Tuesday, October 9, 2018

Afternoon Session

14:00-14:30

Mojtaba Haghighatlari (Pfizer Central Research)

Accelerated discovery of high-refractive-index materials, using molecular modeling and machine learning

14:30-15:00

Francisco Matos (Max Planck Institute for Plasma Physics)

Gaussian Process Tomography with Deep Neural Networks

Thursday, October 11, 2018

Afternoon Session

14:00-14:30

Katherine Breen (NASA)

Developing a Surrogate Model for SWAT with Remotely Sensed Soil Moisture Using Python

14:30-15:00

James Levitt (University of Texas at Austin)

Sampling for Hierarchical Approximation of Kernel Matrices

Tuesday, October 23, 2018

Afternoon Session

14:00-14:30

Bastian Bohn (Rheinische Friedrich-Wilhelms-Universität Bonn)

Optimal data transformation for sparse grids

14:30-15:00

Justin Sunu (Claremont Graduate University)

Unsupervised vehicle recognition using incremental reseeding of acoustic signatures

Thursday, October 25, 2018

Afternoon Session

14:00-14:30

Marco Duarte (University of Massachusetts Amherst)

Graph and Autoencoder-Based Unsupervised Feature Selection with Broad and Local Data Structure Preservation

14:30-15:00

Saerom Park (Sungshin Women's University)

AI and Security: Adversarial Attacks and Defenses

Thursday, November 1, 2018

Afternoon Session

14:00-14:30

Ionut-Gabriel Farcas (Virginia Tech)

Adaptive multilevel stochastic collocations for uncertainty propagation and Bayesian parameter estimation

14:30-15:00

Longfei Gao (King Abdullah Univ. of Science and Technology (KAUST))

Machine Learning for PDE-based Applications?

Tuesday, November 13, 2018

Afternoon Session

14:00-14:30

Jinlong Wu (California Institute of Technology)

Data-Driven Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning

Tuesday, November 20, 2018

Afternoon Session

14:00-14:30

Pietro Grandinetti (LegalKite)

Control of large-scale traffic networks

14:30-15:00

David Kim (McMaster University)

Insights From Linking Schrödinger Equation to Machine Learning

Tuesday, December 4, 2018

Afternoon Session

14:00-14:30

Chee Wei Tan (City University of Hong Kong)

Network Centrality as Statistical Inference in Large Networks

Thursday, December 6, 2018

Afternoon Session

14:00-14:30

Samuel Araki (Air Force Research Laboratory)

Overview of AFRL's Modeling Activities on Electric Propulsion Devices

14:30-15:00

Eder Sousa (The RAND Corporation)

Application of Machine Learning algorithms to In-Space Propulsion

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