Cheryl Xu
Professor
- Phone: (919) 515-5271
- Email: cxu24@ncsu.edu
- Office: Engineering Building III (EB3) 3156
- Website: https://mae.ncsu.edu/cxu/
Dr. Chengying “Cheryl” Xu’s research interests are advanced manufacturing of multifunctional materials, sensor design and manufacturing in harsh environments, process optimization, and sensor-based health monitoring and control through artificial intelligence (AI). Dr. Xu is actively researching materials processing and advanced manufacturing and has attracted high research funding. She co-authored a textbook (Intelligent Systems: Modeling, Optimization and Control, CRC Press, 2008) and has published five book chapters. Dr. Xu chaired the 1st NSF National Wireless Research Collaboration Workshop in 2015. Currently she is serving as the Editor-in-Chief at Nature Portfolio: npj Advanced Manufacturing. She has served as an Associate Editor of ASME Transactions since 2015.
Dr. Xu’s research focuses on manufacturing multifunctional ceramic materials, especially on their electrical/dielectric, mechanical, and thermal properties, and how to manufacture such materials for high-temperature applications. Such studies provide great flexibility in design and manufacturing and meet a wide range of application requirements, such as high-temperature sensor design for extreme conditions, etc. The ability to effectively integrate these technologies and materials into applicable devices is critical for industry and federal government laboratories. Her research interests have been in the field of advanced manufacturing and applying the knowledge and experience to help bring engineering components and devices for next-generation energy, environmental, aerospace, and defense applications, with specific focuses on the following aspects:
- Research and development of novel multifunctional materials with desirable structures/functionalities;
- Developing practical/robust manufacturing processes to transform new materials into engineering components and devices;
- Understanding the fundamental physics and chemistry of advanced manufacturing processes;
- Integrating artificial intelligence (AI) / machine learning (ML) into manufacturing processes.