Machine Learning, Embedding, and Dynamics of Many-Electron States in Molecules and Materials
SCHEDULE
9:30 am - 10:00 am: Reception and Coffee with Pastry
10:00 am - 11:20 am: Michele Pavanello, Rutgers University at Newark
“Making and breaking electronic structures: Opportunities from machine learning and orbital-free embedding”
colab notebook:
https://colab.research.google.com/drive/1QEQYAaRxkyIZJBkxaPOJGPw9VYwknQ_3#scrollTo=pNS0PfoGIXlV
https://doi.org/10.1038/s41467-023-41953-9
https://pubs.acs.org/doi/full/10.1021/acs.jpclett.2c01424
https://pubs.acs.org/doi/full/10.1021/acs.jctc.2c00698
https://journals.aps.org/prb/abstract/10.1103/PhysRevB.104.235110
11:30 am - 12:50 pm: Qin Wu, Brookhaven National Laboratory
“Interpreting transient kinetics infrared study of CO adsorption through DFT and machine learning methods”
https://doi.org/10.1063/5.0110313
1:00 pm - 2:30 pm: Lunch & Discussion
2:30 pm - 3:50 pm: Tianyu Zhu, Yale University
“Predicting materials spectroscopy from quantum embedding and machine learning”
https://journals.aps.org/prx/abstract/10.1103/PhysRevX.11.021006
https://pubs.acs.org/doi/10.1021/acs.jpclett.2c02534
https://arxiv.org/abs/2310.03920
4:00 pm -5:20 pm: Joshua Kretchmer, Georgia Tech
“Real-time simulations of non-equilibrium electron dynamics”
5:20 pm - 6:00 pm: Discussion
ORGANIZERS
Seogjoo J. Jang, PhD
Professor, Department of Chemistry and Biochemistry
Queens College, City University of New York