11:00 am – 11:05 am—Workshop Welcome
11:05 am – 12:05 pm—Session III: Machine Learning and Materials Modeling
11:05 am - 11:35 am—Application of Statistical Approaches to Proton-Conducting Phosphate Glasses: Study of the Effect of Oxide Components on Proton Mobility and Thermal Stability
Speaker:
Takahisa Omata, Tohoku University
11:35 am – 12:05 pm—Materials Design from Atomistic Simulations and Electron Microscopy Guided by Explainable Scientific Machine Learning
Speaker: Ayana Ghosh, Oak Ridge National Laboratory
12:05 pm – 2:20 pm—Session IV: Machine Learning and Materials Characterization
12:05 pm – 12:35 pm—Theory-informed AI/ML for Materials Characterization
Speaker: Maria Chan, Argonne National Laboratory
12:35 pm - 1:05 pm—Deep Learning Defect Detection in Electron Microscopy of Radiation Damage
Speaker: Dane Morgan, University of Wisconsin–Madison
1:05 pm - 1:20 pm—Break
1:20 pm – 1:50 pm—Machine Learning for High-Throughput Characterization of Nanoelectronics
Speaker: Matthew Hauwiller, Seagate Technology
1:50 pm – 2:20 pm—Boosting Prediction of NMR Properties in Disordered Solids with Machine Learning
Speaker: Thibault Charpentier, Université Paris–Saclay
2:20 pm—Closing Remarks
Please note: Session times are listed in Eastern Time and the above schedule is tentative.