9am | Welcome and Intro |
9am - 10am MST | AI4S Featured Speaker: Rick Stevens, Associate laboratory director for Computing, Environment and Life Sciences at Argonne National Laboratory Session chair: Gokcen Kestor, Pacific Northwest National Laboratory |
10am - 10:30am MST | Morning Break |
10:30am - 11:30am MST | AI4S Featured Speaker: Anima Anandkumar, Bren Professor of Computing at California Institute of Technology and a director of Machine Learning research at NVIDIA. Session chair: Murali Ermani, Argonne National Laboratory |
11:30am - 11:50am MST | Paper: A Comparison of Mesh-Free Differentiable Programming and Data-Driven Strategies for Optimal Control under PDE Constraints
(Roussel Desmond Nzoyem Ngueguin, David A.W. Barton, and Tom Deakin.) Session chair: Dong Li |
11:50am - 12:10pm MST | Paper: Toward Foundation Models for Materials Science: The Open MatSci ML Toolkit (Kin Long Kelvin Lee, Carmelo Gonzales, Matthew Spellings, Mikhail Galkin, Santiago Miret, and Nalini Kumar.) Session chair: Dong Li |
12:10pm - 12:30pm MST | Paper: Protein Generation via Genome-Scale Language Models with Bio-Physical Scoring (Gautham Dharuman, Logan WardHeng Ma, Priyanka V. Setty, Ozan Gokdemir, Sam Foreman, Murali Emani, Kyle Hippe, Alexander Brace, Kristopher Keipert, Thomas Gibbs, Ian Foster, Anima Anandkumar, Venkatram Vishwanath, and Arvind Ramanathan.) Session chair: Dong Li |
12:30pm - 2pm MST | Lunch Break |
2pm - 2:20pm MST | Paper: Accelerating Particle and Fluid Simulations with Differentiable and Interpretable Graph Networks for Solving Forward and Inverse Problems (Krishna Kumar and Yonjin Choi) Session chair: Murali Krishna Emani |
2:20pm - 2:40pm MST | Paper: Enabling Performant Thermal Conductivity Modeling with DeePMD and LAMMPS on CPUs (Nariman Piroozan and Nalini Kumar) Session chair: Murali Krishna Emani |
2:40pm - 3pm MST | Paper: Machine Learning Applied to Single-Molecule Activity Prediction (Kendric Hood and Qiang Guan) Session chair: Murali Krishna Emani |
3pm - 3:30pm MST | Afternoon Break |
3:30pm - 3:50pm MST | Paper: Tournament-Based Pretraining to Accelerate Federated Learning (Matt Baughman, Nathaniel Hudson, Ryan Chard, Andre Bauer, Ian Foster, and Kyle Chard) Session chair: Murali Krishna Emani |
3:50pm - 4:10pm MST | Paper: Elastic Deep Learning through Resilient Collective Operations (Jiali Li, George Bosilca, Aurelien Bouteiller, and Bogdan Nicolae) Session chair: Murali Krishna Emani |
4:10pm - 4:30pm MST | Paper: Toward Rapid Autonomous Electron Microscopy with Active Meta-Learning (Gayathri Saranathan, Martin Foltin, Aalap Tripathy, Maxim Ziatdinov, Ann Mary Justine Koomthanam, Suparna Bhattacharya, Ayana Ghosh, Kevin Roccapriore, Sreenivas Rangan Sukumar, and Paolo Faraboschi) Session chair: Murali Krishna Emani |
4:30pm - 4:45pm MST | Paper: Autotuning Apache TVM-Based Scientific Applications Using Bayesian Optimization (Xingfu Wu, Praveen Paramasivam, and Valerie Taylor) Session chair: Wenqian Dong |
4:45pm - 5pm MST | Paper: Enhancing Heterogeneous Federated Learning with Knowledge Extraction and Multi-Model Fusion (Duy Phuong Nguyen, Sixing YuJ. Pablo Muñoz, and Ali Jannesari) Session chair: Wenqian Dong |
5pm - 5:15pm MST | Paper: Entropy-Driven Optimal Sub-Sampling of Fluid Dynamics for Developing Machine-Learned Surrogates (Wesley Brewer, Daniel Martinez, Muralikrishnan Gopalakrishnan Meena, Aditya KashiKatarzyna Borowiec, Siyan Liu, Christopher Pilmaier, Greg Burgreen, and Shanti Bhushan) Session chair: Wenqian Dong |
5:15pm - 5:30pm MST | Paper: Tencoder: Tensor-Product Encoder-Decoder Architecture for Predicting Solutions of PDEs with Variable Boundary Data (Aditya Kashi) Session chair: Wenqian Dong |
5:30pm MST | Closing Dong Li, University of California, Merced |
August 18 (11:59pm, AOE), 2023 (the deadline has been extended)
September 22, 2023
September 29, 2023