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Mahmood Mamivand - Deep Learning for Materials Development
October 13, 2022 @ 10:30 am MDT
Assistant Professor of Mechanical Engineering
Boise State University
Deep Learning for Materials Development
Dr. Mamivand is an assistant professor in Mechanical and Biomedical Engineering at Boise State University. Dr. Mamivand’s research focuses on developing physics-based and data-driven models to understand the inter-relationships between chemistry, processing, structure, and property in materials. He received his Ph.D. in Mechanical Engineering from Mississippi State University and had postdoctoral training at the University of Wisconsin-Madison before joining Boise State. He is the recipient of the NSF CAREER award and distinguished graduate scholar award from Bagley College of Engineering at Mississippi State University.
Developing novel materials has been a constant challenge throughout human history. Traditionally, materials development happened by chance and experiment. Later physics-based computational techniques were employed to speed up the materials development process. In the past decade, machine learning has introduced a new paradigm for materials development. Materials informatics in combination with experiments and computational models can dramatically accelerate novel materials discovery. In this presentation, I will talk about the Computational Materials Design lab efforts toward developing novel non-rare-earth-based permanent magnets and how deep learning opens a new horizon for materials chemistry and processing history prediction.