When
Thursday, May 1, 2025 at 2:00 p.m. (MST)
Mohamed Shafae
Assistant Professor of Systems and Industrial Engineering
University of Arizona
"Building the Future of Manufacturing: Intelligent, Secure, and Autonomous Cyber-Physical Systems"
ENGR 301
Abstract: This seminar will offer an overview of the research activities conducted at the Cyber-Physical Manufacturing (CyPhyMan) Systems Lab at the University of Arizona, highlighting innovative solutions and methodologies spanning multiple facets of Smart Manufacturing Systems. Attendees will explore key research initiatives, including comprehensive approaches for cybersecurity threat characterization, risk modeling, and resilient detection and mitigation strategies for manufacturing cyber-physical systems; the development of advanced data analytics methods for real-time detection and prediction of microstructural and process defects in additive manufacturing of nickel-based superalloys; advanced process monitoring and optimization strategies for hybrid additive-subtractive manufacturing; autonomous data-driven quality control frameworks tailored for continuous water treatment systems. The talk will also showcase the state-of-the-art equipment and experimental capabilities at the CyPhyMan Lab, demonstrating how interdisciplinary research and advanced technologies are converging to shape the future of manufacturing toward enhanced intelligence, security, and autonomy.
Bio: Mohamed Shafae is an assistant professor in the Department of Systems and Industrial Engineering at The University of Arizona, where he directs the Cyber-Physical Manufacturing Systems (CyPhyMan) Lab and is an affiliate of the Interdisciplinary Program in Applied Mathematics. Shafae earned his PhD and MS degrees in Industrial Engineering from Virginia Tech in 2018, after completing his M.Sc. and B.Sc. degrees from Alexandria University in Egypt. His research lies at the intersection of Artificial Intelligence, advanced manufacturing, and cyber-physical systems. Shafae has led and contributed to several multi-institutional research initiatives, supported by NASA, the U.S. Army Corps of Engineers, and Arizona's Technology and Research Initiative Fund, where he has helped develop machine learning methods for monitoring and quality assurance of metal additive manufacturing in aerospace applications; cyber-physical systems security tools for risk assessment, prevention, detection, and mitigation; and AI-driven autonomous water treatment and reuse systems for decentralized resilient infrastructure. He has also collaborated on applied research projects with a wide range of industry leaders, including IBM, Honeywell, Lockheed Martin and Roche.