Nastaran has extensive experience with computational methods such as machine-learning techniques and molecular dynamic simulations. Her research focuses on applying advanced linear and nonlinear machine learning techniques such as multiple linear regression and artificial neural networks to explore the relationship between structure and photo-luminescent properties for photovoltaic materials. She also uses classical molecular dynamics simulations and ab initio techniques to examine the mutual orientation and properties of organic photo-dyes in solar cell matrices.
Qualifications:
PhD Chemistry, La Trobe University, Australia (2018)
MSc Chemistry, K.N.Toosi University of Technology, Iran (2012)
BSc Chemistry, Mazandaran University, Iran (2008)
