Cheryl Xu

Dr. Chengying “Cheryl” Xu’s research interests are advanced manufacturing of multifunctional materials, sensor design and manufacturing in harsh environments, process optimization, sensor-based health monitoring and control through artificial intelligence (AI). Dr. Xu is active in conducting research in the field of materials processing and advanced manufacturing and has attracted a high level of 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. She serves as an Associate Editor of ASME Transactions from 2015.

Dr. Xu’s research focus is manufacturing of 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, electromagnetic (EM) absorption material, high temperature radio frequency (RF) transparent materials, metamaterial designs for extreme conditions, etc. The capabilities to effectively integrate these technologies and materials into applicable devices are critical for industry and the federal government laboratories. Her research interests have been in the field of advanced manufacturing, and to apply 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.