Mohammadreza Karamad

LAB INFORMATION

• LAB: B8220
• PHONE: 778-782-8056
• Research Website

RESEARCH

Recent advancements in quantum-mechanical (QM) methods, notably density functional theory (DFT), have significantly enhanced our understanding of materials properties, enabling the prediction of these properties a priori. High-throughput QM calculations, in particular, have established a robust framework for the exploration of new materials. Additionally, the recent progress in Machine Learning (ML) methods has facilitated the exploration of the vast phase space of materials, characterized by structural and compositional degrees of freedom, leading to breakthroughs in materials discovery.

My primary research focus lies at the intersection of computational materials science and ML. I am particularly interested in leveraging these approaches for the development of advanced energy materials relevant to clean energy technologies, such as hydrogen storage and catalysis.

We are looking for enthusiastic undergraduate and graduate students to join our program!

PUBLICATIONS

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