Rate My Professor Farhad Ameri

Farhad Ameri is an Associate Professor in the School of Manufacturing Systems and Networks within the Ira A. Fulton Schools of Engineering at Arizona State University, where he joined in 2023. He serves as Director of the Semantic Computing Lab and program chair for the Manufacturing Engineering PhD program. Ameri earned his PhD in Manufacturing Engineering from the University of Michigan in 2006, as well as B.S. and M.S. degrees in Industrial and Systems Engineering. His academic career emphasizes advancing manufacturing education through courses in design for manufacturing, product development, and design of automated manufacturing systems, employing active learning, project-based, and self-directed techniques.

Ameri's research focuses on semantic artificial intelligence and ontology engineering applied to digital manufacturing systems, supply networks, knowledge graphs, digital twins, and smart manufacturing automation. He is a founding member of the Industrial Ontology Foundry (IOF), promoting ontology standardization in manufacturing, and a member of ASME and IFIP WG 5.7 on Advances in Production Management Systems. His scholarship appears in high-impact venues such as ASME Journal of Computing and Information Science in Engineering, ASME Journal of Mechanical Design, International Journal of Production Research, and ASME Journal of Manufacturing Science and Engineering. Notable works include the book Supply Chain Standardization: An Ontological Approach (2008); edited volumes Advances in Production Management Systems: Production Management for the Factory of the Future and Towards Smart Production Management Systems (both 2019); book chapters like Manufacturing Capability Knowledge Modeling for Intelligent Manufacturing Systems (2014); and recent journal articles such as Ontology-driven integration of advertised and operational capabilities in robots (2025), Automated Pipe Defect Identification in Underwater Robot Imagery with Deep Learning (2025), and Integrating Graph Retrieval Augmented Generation with Large Language Models for Supplier Discovery (2024). His research has garnered over 2600 citations and receives funding from the National Science Foundation, National Institute of Standards and Technology, MxD, and industry sponsors.