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Data-Driven and Multiscale Modeling of Energy and Quantum Materials

Amartya Banerjee, University of California, Los Angeles
Ananya Balakrishna, University of California, Santa Barbara
Vikram Gavini, University of Michigan
This symposium aims to bring together researchers interested in developing computational and data science based techniques that are directed towards understanding the electronic, atomistic and mesoscopic underpinnings of materials of interest to energy and quantum information science applications.
Areas of interest include, but are not limited to, recent progress in:
  1. Numerical and machine learning based methods for first principles, atomistic, microscale and mesoscale modeling of energy and quantum materials.
  2. Formulation, analysis and implementation of coarse-graining techniques, variational methods, data-driven approaches for multiscale and multiphysics problems.
  3.  Applications of the above techniques to effectively predict, characterize, and guide the development of energy and quantum materials.