Day 1 Computer Vision and Robotics Ling Liu-Robust Video Analytics Simon Lapointe-Photodiode-based ML for Laser Powder Bed Fusion Brian Gallagher-ML Driven Material Performance Prediction Nathan Mundhenk-Explaining NN Predictions of Material Strength Industry Use Cases Seid Koric et al.-Confluence of Numerical Modeling Methods and AI in Physics-based Simulations Sam Ansari-Applications of Computer Vision in Banking Process Automation Rajesh Aggarwal-Automated Defect Detection using Deep Learning Bernard Chukwulebe-Leading the Charge in Steel Industry Applications of AI and ML Vic Castillo-Applications of Scientific ML for Manufacturing Processes Rangan Sukumar-Conveged Workflows of HPC, AI and Data in COVID-19 Response Brian Gallagher-ML Driven Material Performance Prediction Keynote - Upadhyay Devesh Upadhyay-ML and Data Science at Ford Process Control and Optimization Joshua Morgan-Application of Framework for Modeling CO2 Capture Jony Castagna-Automated Wing in Tank Inspection Andi Wang-Holistic Modeling and Analysis of Multistage Manufacturing Processes Wolfgang Gentzsch-Repairing Cardiac Valve Leakage Jianjun Shi-ML Enabled Quality Improvement in Smart Manufacturing Systems Day 2 Data Sets-Standards, Augmentation, Curation Joe Morris-the DOE SMART Initiative Brian Au-Autonomous Multimodal Manufacturing Optimization via Digital Twins Keynote-Abbeel Pieter Abbeel-Towards a General Solution for Robotics ML Software and Hardware Ecosystem Rangan Sukumar-Survival of the Fittest amidst the Cambrian Explosion of Processor Architectures Edward Rusu-Admiral-Connecting RL Libraries with HPC Simulations Kevin Kissell-Enabling non-Experts with Google ML Hardware and Services ML Solution Taxonomies and Workflows Joseph Koning-Merlin ML Workflow for HPC Eliu Huerta-From HPC to the Edge to Enable Accelerated and Reproducible AI Discovery Romit Maulik-Scalable Neural Architecture Search using DeepHyper Claus-Peter Rrueckemann-Coherent Knowledge Solutions from Prehistory to Future Brian Silva et al.-Integrating ML Insights into Work Bowei Xi-Adversarial ML and Attacks against Deep NN Day 3 Physics-Constrained Learning Tom Desautels-Creating a Platform for Rapid Computational Antibody Design via ML, HPC, and Laboratory Subarna Bhattachyaryya-Using AI to Better Predict Future Climate to Drive Better Business Decisions Felipe Viana-Prognosis and Health Management with Digital Twins and Hybrid Physics Informed NN Daning Huang-Physics-Infused Differential-Algebraic Reduced-Order Models for Multi-Disciplinary Systems Youngsoo Choi-Hyper-reduced nonlinear manifold reduced order model
