UW Composites Group

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.

research activities

Recent Linkedin Posts

Today marked the first class of the Spring Quarter with my Junior students diving into Materials Science and Engineering. There’s something special about that first day...

I recently published an article on the ASC website, reflecting on the amazing 2024 ASC Conference in San Diego! It was incredible to connect with so many passionate researchers...

I had the wonderful opportunity to host esteemed visitors from Toray Industries, Inc. at the University of Washington, including CTO Satoru Hagiwara, along with several of their executive and technical...

Exciting activities are happening at UW Advanced Composites Center. We have just received our carbon fiber composite tool for Automated Fiber Placement (AFP) production ...

It was such a pleasant experience introducing about 1,000 freshman engineers at University of Washington to manufacturing and automation, along with two other great panelists ...

Online Courses

This 9-lecture series introduces the principles of Physics-Informed Machine Learning (PIML) and its application to solving complex multi-physics problems in science and engineering.

This 8-lecture series on composite structural engineering is designed for training the next generation of aerospace engineers, focusing on the certification of composite civil aircraft structures per FAA curriculum standards.

Recent Youtube Videos

Materials Science and Engineering: Transforming Aerospace Manufacturing

AI in Aerospace: From Material Innovation to Autonomy in Factories and Flight

Research Spotlight: Autonomous Robots & AI for Advanced Materials Testing

Recent Awards

Navid Zobeiry recives the certificate for Boeing Distinguished Researcher & Scholar Seminar Series (B-DRASS).

Caleb Schoenholz takes SAMPE URS third Best Paper Award.

Selected Publications

Portales P., Gray A., Zobeiry N. (2025). Efficient characterization and optimization of pyrolysis in carbon-carbon composites through machine learning, Composites Part A, 190: 108664.

Fontes A., Zobeiry N., Shadmehri F. (2025). Theory-guided machine learning for thermal modeling of in-situ automated fiber placement of thermoplastic composites, Composites Science and Technology, 260:110987.

Schoenholz, C., Zappino, E., Petrolo, M., & Zobeiry, N. (2024). Efficient analysis of composites manufacturing using multi-fidelity simulation and probabilistic machine learning. Composites Part B: Engineering, 280, 111499.

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.

Picazo, P. P., Cheng, R., Gray, A., & Zobeiry, N. (2024). A Machine Learning-based Accelerated Pyrolysis Characterization and Optimization of High-temperature Composites. SAMPE Journal, 60(2).

Schoenholz, C., & Zobeiry, N. (2024). Investigating the Impacts of Processing Variability on Tool-part Interaction for Interply-toughened Aerospace Composites using a Novel Shear Technique. Composites Part A: Applied Science and Manufacturing, 178, 107973.

Schoenholz, C., & Zobeiry, N. (2024). An Accelerated Process Optimization Method to Minimize Deformations in Composites Using Theory-guided Probabilistic Machine Learning. Composites Part A: Applied Science and Manufacturing, 176, 107842.

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.

Wynn, M., & Zobeiry, N. (2022). Investigating the Effect of Temperature History on Crystal Morphology of Thermoplastic Composites Using In Situ Polarized Light Microscopy and Probabilistic Machine Learning. Polymers, 15(1), 18.

Freed, Y., Salviato, M., & Zobeiry, N. (2022). Implementation of a probabilistic machine learning strategy for failure predictions of adhesively bonded joints using cohesive zone modeling. International Journal of Adhesion and Adhesives, 118, 103226.

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.

Reiner, J., Vaziri, R., & Zobeiry, N. (2021). Machine learning assisted characterisation and simulation of compressive damage in composite laminates. Composite Structures, 273, 114290.

Zobeiry, N., & Humfeld, K. D. (2021). A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications. Engineering Applications of Artificial Intelligence, 101, 104232.

Zobeiry, N., Lee, A., & Mobuchon, C. (2020). Fabrication of transparent advanced composites. Composites Science and Technology, 197, 108281.

Zobeiry, N., Reiner, J., & Vaziri, R. (2020). Theory-guided machine learning for damage characterization of composites. Composite Structures, 246, 112407.