UTA Engineer Receives $500,000 NSF CAREER Award for AI Research
Chen Kan from UTA awarded NSF CAREER grant for AI innovations in manufacturing.
Key Points
- • Chen Kan receives a $500,000 NSF CAREER Award for AI research.
- • Research focuses on improving additive manufacturing of metamaterials.
- • Utilizes sensing devices and machine learning to analyze manufacturing processes.
- • Effective for small- to medium-sized companies in implementing advanced techniques.
Chen Kan, an assistant professor at the University of Texas at Arlington (UTA), has been awarded the $500,000 National Science Foundation (NSF) CAREER Award for his innovative work in artificial intelligence (AI) and additive manufacturing. This prestigious award recognizes Kan's potential to integrate education with research, as he focuses on enhancing the production of metamaterials, which have applications in aerospace and healthcare.
Kan's research aims to tackle the challenges posed by manufacturing imperfections that can affect final product quality. Using advanced sensing technologies, he plans to gather data throughout the manufacturing process, applying machine learning techniques to analyze this data. The goal is to develop a scalable algorithm applicable to various types of metamaterials, making it an invaluable tool especially for small- to medium-sized enterprises.
Since joining UTA in 2018, Kan has concentrated on areas like advanced manufacturing, quality control, and anomaly detection. His chair, Sampson Gholston, praised the impact of his work within the department and UTA, a university noted for its prominent research contributions, generating an economic impact of approximately $28.8 billion annually in Texas. This accolade not only highlights Kan’s individual achievement but reflects UTA's commitment to fostering significant research endeavors as it celebrates its 130th anniversary this year.