ASME

Journal of Computing and Information Science in Engineering

Chenang 
Liu, Ph.D.
Chenang Photo

Areas of Interest

APPLIED ARTIFICIAL INTELLIGENCE
DATA-DRIVEN ANALYTICS
MACHINE LEARNING
SMART MANUFACTURING
Dr. Chenang Liu is an Assistant Professor in the School of Industrial Engineering and Management at Oklahoma State University. He earned his Ph.D. degree in Industrial and Systems Engineering from Virginia Tech in 2019. He also received his master’s degree in Statistics from Virginia Tech in 2017 and double bachelor’s degrees from Zhejiang University in 2014. His research interests include data-driven analytics and machine learning-enabled modeling to advance smart manufacturing, healthcare, and service systems, as well as applied artificial intelligence for engineering applications. His work has won multiple best paper and poster awards at the IISE and INFORMS conferences.

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Special Issue on Geometric Data Processing and Analysis for Advanced Manufacturing

Geometric information, such as three-dimensional (3D) shapes and network topologies, has been increasingly explored in manufacturing research. For example, characterizing geometric information in 3D-printed parts, in-situ or ex-situ, opens opportunities for defect detection, quality improvement, and product customization. However, geometric data mining remains critically challenging. Geometric information is embedded in complex data structures, such as 3D point clouds, graphs, meshes, voxels, high-dimensional images, and tensors, which possess challenges for analysis due to their high-dimensionality, high-volume, unstructured, multimodality characteristics. Additional challenges stem from compromised data quality (e.g., noisy and incomplete data), the need for registration, etc.

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