Navid Zobeiry

Dr. Navid Zobeiry is an Associate Professor in Materials Science & Engineering at the University of Washington, with an adjunct role in Aeronautics & Astronautics. His research integrates materials science, data science, and advanced manufacturing to address aerospace challenges, focusing on smart testing, manufacturing, and engineering methods using machine learning and physics-based models. He holds patents in AI software for aerospace applications and has been recognized with awards such as the Boeing Certificate of Appreciation (2024) and the SAMPE URS 3rd Best Paper Award (2022).

Education: PhD from University of British Columbia (UBC), MSc from UBC, BSc from University of Tehran. Prior to UW, he was a Research Associate and Lecturer at UBC.

Research interests span composite materials, failure analysis, scientific machine learning, and uncertainty quantification in aerospace. His work emphasizes probabilistic ML frameworks for material characterization and process optimization.

Recent articles focus on composite manufacturing optimization, process-induced deformations, and ML-driven thermal modeling. His publications highlight advancements in pyrolysis characterization, tool-part interaction analysis, and outlier detection in manufacturing processes.

Awards include Boeing’s D-DRASS recognition (2024, 2019), a teaching award (2020), and UBC’s President’s Award (2009). He advises graduate students like C. Schoenholz and collaborates with aerospace companies on patented technologies.

Labs/Teams: Composites Group at UW, leading projects on AI in manufacturing and material certification. Active in industry partnerships for applied research.