Seyed Jamaleddin Mostafavi Yazdi, Ph.D.

Dr. Seyed Jamaleddin Mostafavi Yazdi is an Assistant Professor of Mechanical Engineering at Kettering University. He earned his Ph.D. in Mechanical Engineering from Kyungpook National University, Daegu, South Korea, in 2019. Following his doctorate, he served as a postdoctoral researcher at the Artificial Intelligence and Computed Diagnosis Lab (AICD) in South Korea from March 2019 to February 2020. He then continued as a postdoctoral researcher in the Mechanical Engineering Department at Kettering University from February 2020 to May 2022.

Dr. Mostafavi Yazdi’s research interests span multiple interdisciplinary fields, including:

• Mechanics of Materials & Metamaterials: Investigating the mechanical behavior of advanced materials, composite structures, and metamaterials for tailored mechanical and acoustic properties.
• Computational Mechanics & Finite Element Analysis (FEA): Developing numerical models to study stress-strain behavior, fracture mechanics, and structural responses under various loading conditions.
• Machine Learning & Data-Driven Modeling: Applying AI and machine learning techniques to material characterization, failure prediction, and structural health monitoring.
• Design Optimization & Topology Optimization: Utilizing optimization algorithms to enhance material efficiency in structural components, additive manufacturing, and lightweight design.
• Additive Manufacturing & Digital Fabrication: Exploring AI-driven design techniques for next-generation materials and structures fabricated through 3D printing and advanced manufacturing processes.
• Vibrational Analysis & Acoustics: Studying wave propagation, noise reduction, and dynamic response in engineered materials and structures.
• Hybrid Experimental-Computational Approaches: Integrating Digital Image Correlation (DIC), Acoustic Emission Analysis, and AI-based predictive modeling to improve material performance assessment.

Research Focus & Contributions

Dr. Mostafavi Yazdi is dedicated to solving complex engineering challenges at the intersection of solid mechanics, computational modeling, and artificial intelligence. His work emphasizes synergistic integration between theoretical modeling, numerical simulations, and experimental validation to advance the design and performance of novel engineering materials and structures.

Select Publications & Research Contributions

• "AI-Driven Topology Optimization for Lightweight and High-Performance Structures" – Explores machine learning-assisted structural optimization for aerospace and automotive applications.
• "Metamaterial-Based Vibration and Noise Control: A Computational and Experimental Investigation" – Discusses the application of engineered materials to manipulate wave propagation for noise and vibration reduction.
• "Deep Learning for Predicting Mechanical Properties of Composite and Metamaterials" – Presents a hybrid AI-FEA framework for accurate material property prediction.
• "Inverse Problem Solving in Structural Mechanics Using Neural Networks" – Investigates AI-driven methods for non-destructive evaluation and damage detection in engineering structures.
• "Additive Manufacturing and AI: A New Frontier in Smart Material Design" – Examines AI-assisted material selection and manufacturing techniques for enhanced structural performance.

Dr. Mostafavi Yazdi’s interdisciplinary approach bridges mechanics, AI, and optimization techniques, driving innovation in materials, design, and advanced manufacturing. He believes that the integration of computational mechanics, machine learning, and novel experimental techniques is key to engineering the next generation of smart materials and structures.