About the author
Professor, engineering researcher, and author of Machine Learning for Engineering Applications.
Dr. Yan Jin is Professor of Aerospace and Mechanical Engineering at the University of Southern California and Director of the USC IMPACT Laboratory.
He received his Ph.D. in Naval Engineering from the University of Tokyo and conducted postdoctoral research at Stanford University. Before joining the USC faculty, he worked as a Senior Research Scientist at Stanford.
His research spans artificial intelligence and machine learning in engineering design and manufacturing, design theory and methodology, multiagent and self-organizing systems, organization modeling and project management, and collaborative engineering. His current interests include AI and machine learning in systems engineering, design methods, and complex engineered systems.
Machine Learning for Engineering Applications brings these perspectives together for students, practicing engineers, and instructors. The book connects mathematical and computational methods with physical knowledge, engineering constraints, validation, and system-level decision making.
Selected distinctions
His honors include the 2025 ASME Design Theory and Methodology Award, the NSF CAREER Award, the Northrop Grumman Excellence in Teaching Award, and multiple best-paper awards. He has been an ASME Fellow since 2010.
Professional service
Dr. Jin served as Editor-in-Chief of AIEDAM (AI for Engineering Design, Analysis, and Manufacturing) and has held editorial roles with Design Science, the Journal of Mechanical Design, and other engineering design and informatics journals.
USC IMPACT Laboratory
The IMPACT Lab develops intelligent machines and data-driven AI systems for engineering design, analysis, manufacturing, autonomous operations, and self-organizing engineered systems.
Visit the IMPACT Lab