All times are in EDT.
| Time | Details | |
|---|---|---|
Tuesday, April 18, 2023 | ||
| 7:30 a.m. | Badging, Registration and Working Breakfast | |
| 8:00 a.m. | Pradeep Ramuhalli, Oak Ridge National Laboratory Welcome and Introduction | |
| 9:00 - 11:10 a.m. | Technical Session 1: Digital Twin Model Development and Lifecycle Management Session Chair: Katarzyna Swirydowicz | |
| 9:00 a.m. | Invited Speaker 1-1: Ronald Boring, Idaho National Laboratory Explainable Natural and Artificial Intelligence: The Human in the Loop | |
| 9:30 a.m. | Speaker 1-1: Guannan Zhang, Oak Ridge National Laboratory Transferable Neural Feature Spaces for Partial Differential Equations | |
| 9:50 a.m. | Speaker 1-2: Kibaek Kim, Argonne National Laboratory APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning | |
| 10:10 a.m. | Break | |
| 10:30 - 11:45 a.m. | Flash Talks Machine Learning-Based Compact Modeling of Multi-State Devices Merging Physics with ML for HTGR Plant Component Design and Health Monitoring Towards the Development of a Level 5 Digital Twin of an Exascale Supercomputer Application of an AI-Based Digital Twin of a Combustion Engine within a Physics-Informed Framework: A Case Study Towards Human-Centric Digital Twin of Machine Tool by a System-Driven AI Engineering Approach Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems | |
| 11:45 a.m. | Pradeep Ramuhalli, Oak Ridge National Laboratory Breakout Session Introductions (Working Lunch) | |
| 1:00 - 2:00 p.m. | Technical Session 2: Assured Digital Twins Session Chair: Kishan Rajput | |
| 1:00 p.m. | Speaker 1-3: Shady Ahmed, Pacific Northwest National Laboratory Multifidelity Operator Networks for Closure Modeling in Multiscale Systems | |
| 1:20 p.m. | Speaker 1-4: Arvind Mohan, Los Alamos National Laboratory Non-Intrusive Machine Learning Models of PDEs with Differentiable Programming: An Interpretability Study | |
| 1:40 p.m. | Speaker 1-5: Mark Cianciosa, Oak Ridge National Laboratory Machine Learning Proxy Model Refinement using Interference Uncertainty Estimation | |
| 2:00 - 3:15 p.m. | Flash Talks Gaussian Process Port-Hamiltonian Systems Thomas Beckers, Vanderbilt University A Sustainable Machine Learning Framework for SNS Continual Learning for Physical Systems Uncertainty Quantification in Assessing Storm Surges Machine Learning for Joint Performance Prediction In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD Learning Multi-Scale Diffusion Fields Using Satellite-Observed Aerosol Trajectories | |
| 3:15 p.m. | Break | |
| 3:30 p.m. | Breakouts | |
| 4:45 p.m. | Poster Setup | |
| 5:00 p.m. | Welcome Reception and Poster Session | |
| 7:00 p.m. | Day 1 Ends | |
Wednesday, April 19, 2023 | ||
| 7:30 a.m. | Badging, Registration, and Breakfast | |
| 8:00 a.m. | Pradeep Ramuhalli, Oak Ridge National Laboratory Welcome and Agenda Overview / Introduction | |
| 8:30 a.m. | Keynote: Lynne Parker, University of Tennessee Knoxville AI Policies and Opportunites | |
| 9:30 a.m. | Break | |
| 10:00 - 11:30 a.m. | Technical Session 3: Sensors and Data Management Session Chair: Prasanna Balaprakash | |
| 10:00 a.m. | Invited Speaker 2-2: Rao Kotamarthi, Argonne National Laboratory Climate and Weather Modeling Using AI | |
| 10:30 a.m. | Speaker 2-6: Miguel Bessa, Brown University Cooperative Data-Driven Modeling | |
| 10:50 a.m. | Speaker 2-7: Rebekah White, Sandia National Laboratory Optimal Sensor Placement for Maximizing Information Regarding Optimization Objectives | |
| 11:10 a.m. | Speaker 2-8: Prasanna Balaprakash, Oak Ridge National Laboratory Neural Architecture Search for Scientific Machine Learning with Quantified Uncertainty | |
| 11:30 a.m. | Group Photo and Break | |
| 12:00 p.m. | Vincent Paquit, Oak Ridge National Laboratory A Digital Factory for Advanced Manufacturing Technologies (Working Lunch) | |
| 1:00 - 2:30 p.m. | Technical Session 4: Assured Digital Twins Session Chair: Miguel Bessa | |
| 1:00 p.m. | Invited Speaker 2-3: Petros Koumoutsakos, Harvard University AI/Scientific Computing: Algorithmic Alloys for Digital Twins | |
| 1:30 p.m. | Speaker 2-9: Nurali Virani, GE Research Reliable Anomaly Detection with Individual Prediction Reliability | |
| 1:50 p.m. | Speaker 2-10: Chetan Kulkarni, NASA Ames Research Hybrid Modeling for Complex Systems Health Management | |
| 2:10 p.m. | Breakouts | |
| 3:00 p.m. | Break | |
| 4:45 p.m. | Day 2 Ends | |
Thursday, April 20, 2023 | ||
| 7:30 a.m. | Badging, Registration, and Breakfast | |
| 8:00 a.m. | Pradeep Ramuhalli, Oak Ridge National Laboratory Welcome and Agenda Overview | |
| 8:30 - 10:30 a.m. | Technical Session 5: General Topics in Digital Twins Session Chair: Ryan King | |
| 8:30 a.m. | Invited Speaker 3-4: Pascal Van Hentenryck, Georgia Tech The Fusion of Machine Learning and Optimization for Engineering | |
| 9:00 a.m. | Speaker 3-11: William Dawson, Lawrence Livermore National Laboratory Dynamic Bayesian Network Twins for Robust Collaborative Decision Making | |
| 9:20 a.m. | Speaker 3-12: Tia Miceli, Fermilab MLOps for Digital Twins | |
| 9:40 a.m. | Speaker 3-13: Jay Kapat, University of Central Florida Digital Twin for a Gas Turbine | |
| 10:00 a.m. | Speaker 3-14: Jan Drgona, Pacific Northwest National Laboratory Differentiable Programming for Modeling and Control of Dynamical Systems | |
| 10:30 a.m. | Break | |
| 11:00 a.m. | Draguna Vrabie, Pacific Northwest National Laboratory Nurali Virani, GE Research Jan Drgona, Pacific Northwest National Laboratory Gopika Bhardwaj, Fermilab Breakout Reports (Working Lunch) | |
| 1:00 p.m. | Workshop Closeout | |
| 1:00 - 5:00 p.m. | Optional Tours | |