Dr. Yalin Dong
Biography
Dr. Dong joined UA in 2013, shortly after completing his Ph.D. at Purdue University. His current research focuses on artificial intelligence for engineering applications, with an emphasis on designing AI methods that match the needs of specific real-world problems. He works in areas including infrastructure risk prediction, computer vision for automated quality control, physics-informed neural networks, and multi-modal AI for robotic systems that can perceive, reason, and act under uncertainty. His work highlights a central idea: AI is not one model fits all, and effective engineering solutions require architectures designed for the data, physics, and decision demands of each application.
In addition to his research, Dr. Dong is committed to education and innovation at the intersection of engineering and AI. He works to prepare students for the future of intelligent systems by connecting fundamental engineering principles with modern AI tools and applications.
Research
Artificial intelligence, smart manufacturing, robotics, computer vision, and data-driven engineering
Education
- Ph.D. in Mechanical Engineering, Purdue University 2013
- M.S. in Applied Physics, University of Science and Technology of China 2008
- B.S. in Applied Physics, University of Science and Technology of China 2005
Courses
Machine Learning, Dive into Deep Learning, Control Systems Design, Measurements Lab, Finite Element Method, Fluid Mechanics, Engineering Analysis