Mohammed A. Zikry is the Zan Prevost Smith Professor at N.C. State University. His research expertise is in the general areas of multiscale modeling, mechanics of materials, fracture and defect mechanics, computational mechanics, and crystalline plasticity. He has innovated predictive computational, and experimental methodologies that can be used at physical scales ranging from the nano to the macro levels to understand how material behavior can be harnessed for new and significantly improved materials, semi-conductor devices, and structures for systems comprised of metallic alloys, intermetallics, ceramics, composites, biomaterials, and shape memory polymers. He received his Ph.D. from the University of California, San Diego, his M.S. from the Johns Hopkins University, and his B.S. from the University of Kansas. He has also been a Senior Advisor to the Army Research Office, where he initiated and fostered large scale funding opportunities, such as MURIs and Centers of Excellence. He has been involved in numerous leadership positions, such as being the Executive Chair of the American Society of Mechanical Engineering (ASME), and as an advisor to the U.S. Secretary of State, where he was involved in formulating policies for conflict minerals, the Kimberley Process and renewable energy. He has been the Editor of ASME’s Journal of Engineering Materials and Technology, an Editor for Mechanics of Materials, and chair of numerous national and international and advisory boards for universities and DoD and national laboratories. He has been awarded a Professeur, Premiere Classe, Strasbourg University. He has been awarded distinguished alumni awards from the University of California, San Diego, and the University of Kansas. He was also awarded the ASME Robert Thurston Lecture Society Award, which is in recognition of his ground-breaking research accomplishments. He is a Fellow of American Association for the Advancement of Science (AAAS), American Society of Mechanical Engineering (ASME), and the Society of Engineering Science (SES).

• 1. Process-structure-property models for metal additive manufacturing using AI/ML approaches2. An overview on recent processing, metallurgy, and experiments related to microstructure engineering in additive manufacturing3. Dislocations in processing and material behavior4. Machine learning-enabled parametrically upscaled constitutive models for bridging length scales in Ti and Ni alloys5. Data-driven approaches for computational modelling for plasticity, fatigue, and fracture behavior of alloys6. Twin transmission and variant continuity in Mg bicrystals7. Thin-walled LPBF-manufactured Inconel 718 honeycomb structures: Multiscale characterization8. Sample size dependence of mechanical properties in metallic materials9. Intelligent processing and development of high-performance automotive aluminum alloys: Application of physics-based and data-driven modeling10. Comparing the effect of different parameters on the fatigue behavior of aerospace aluminum alloys11. Multiscale model-based design of high-strength alloys with reduced hydrogen embrittlement susceptibility12. Microstructural predictions of how processing and additive manufacturing can affect the mechanical behavior of Inconel alloys13. Breaking boundaries: Deformation processing techniques for the next generation of lightweight and high-strength materials