I am an associate professor in the Materials Science and Engineering department at the University of Washington. I am also an adjunct professor in the Aeronautics and Astronautics department. My research team merges materials science, data science, and advanced manufacturing, focusing on three main areas: 1) Smart testing methods combining physics-informed machine learning and traditional techniques; 2) Smart manufacturing using automation, sensing, and machine learning; 3) Smart engineering methods to optimize and accelerate aerospace design, certification, and qualification through machine learning, automated testing, and multi-fidelity simulations. Our research is anchored in a novel machine learning framework that blends probabilistic and deterministic approaches, integrating engineering data and physical laws. This approach has led to several patented AI innovations.
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Wynn, M., Oster, L., Chase, G., Salviato, M., & Zobeiry, N. (2024). Assessment of the effect of processing parameters on peel failure of laser-assisted automated fiber placed thermoplastic composites. Manufacturing Letters, 40, 93-96. Zappino, E., Masia, R., Zobeiry, N., Petrolo, M., & Carrera, E. (2024). Development of mitigation strategies for process-induced deformations through finite elements. Mechanics of Advanced Materials and Structures, 1-13. Schoenholz, C., Li, S., Bainbridge, K., Huynh, V., Gray, A., & Zobeiry, N. (2023). Accelerated In Situ Inspection of Release Coating and Tool Surface Condition in Composites Manufacturing Using Global Mapping, Sparse Sensing, and Machine Learning. Journal of Manufacturing and Materials Processing, 7(3), 81. Lee, A., Wynn, M., Quigley, L., Salviato, M., & Zobeiry, N. (2022). Effect of temperature history during additive manufacturing on crystalline morphology of PEEK. Advances in Industrial and Manufacturing Engineering, 4, 100085. Humfeld, K. D., Gu, D., Butler, G. A., Nelson, K., & Zobeiry, N. (2021). A machine learning framework for real-time inverse modeling and multi-objective process optimization of composites for active manufacturing control. Composites Part B: Engineering, 223, 109150.