Kevin Carlberg, AI Research Science Manager, Facebook
Nonlinear Model Reduction: Using Machine Learning to Enable Rapid Simulation of Extreme-Scale Physics Models

Rebecca Morrison, Assistant Professor, University of Colorado
Learning Sparse Non-Gaussian Graphical Models

Johannes Brust, Postdoctoral Appointee, MCS/ANL
Limited Memory Structured Quasi-Newton Methods

Elizabeth Qian, PhD Student, MIT
Lift & Learn: A Scientific Machine Learning Framework for Learning Low-Dimensional Models for Nonlinear PDEs

Javad Lavaei, Associate Professor, Department of Industrial Engineering and Operations Research, UC Berkeley
Computational Techniques for Nonlinear Optimization and Learning Problems

Samy Wu Fung, Adjunct Professor, UCLA
A GAN-Based Approach for Solving High-Dimensional Stochastic Mean Field Games

Mike Innes, Software Programmer, Julia Computing
Building Compilers for Numerical Programming

William Moses, PhD Student, MIT
Post-Optimization Automatic Differentiation by Synthesizing LLVM

Cathie Olschanowsky, Assistant Professor, Boise State University
Building High Performance Post-Processing Tools with the Polyhedral Model

Michel Schanen, Assistant Computational Engineering Specialist, MCS/ANL
Solving Power Flow on GPUs in Julia