ASME

Journal of Computing and Information Science in Engineering

Xiaowei 
Yue, Ph.D.
Xiaowei Yue-Photo-2

Areas of Interest

BIG DATA AND ANALYTICS
DATA-DRIVEN ENGINEERING APPLICATIONS
ENGINEERING INFORMATICS
INDUSTRIAL INTERNET OF THINGS
MACHINE LEARNING FOR ENGINEERING APPLICATIONS
MANUFACTURING AUTOMATION
Tsinghua University
Dr. Xiaowei Yue is an associate professor in the Department of Industrial Engineering at Tsinghua University. Prior to that, he was an assistant professor and Grado Faculty Fellow at Virginia Tech. Dr. Yue’s research interests focus on data analytics for intelligent manufacturing. His research has obtained more than 15 best paper awards and two best dissertation awards. Dr. Yue is a recipient of multiple awards, such as IISE Hamed K. Eldin Outstanding Early Career IE in Academia Award, SME Outstanding Young Manufacturing Engineer award, IISE Manufacturing & Design Outstanding Young Investigator Award, and Grainger Frontiers of Engineering Grant Award from the U.S. National Academy of Engineering, etc. Dr. Yue serves as a board director for the IISE DAIS division and QCRE division. He is a member for ASME, and a senior member for IISE and IEEE.

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Announcements

July 17 Spotlight: “Information Embedding in Additively Manufactured Parts Through Printing Speed Control” 

A recording is now available for the July 17, 2024 JCISE Spotlight talk by Professor Jitesh Panchal on paper co-authored with Karim A. ElSayed entitled “Information Embedding in Additively Manufactured Parts Through Printing Speed Control” J. Comput. Inf. Sci. Eng. J. Comput. Inf. Sci. Eng. Jul 2024, 24(7): 071005 (10 pages) Paper No: JCISE-23-1496 https://doi.org/10.1115/1.4065089.

Announcements

June 18, 2024 Spotlight: “Updating Nonlinear Stochastic Dynamics of an Uncertain Nozzle Model Using Probabilistic Learning With Partial Observability and Incomplete Dataset”

A recording is now available on Youtube for the June 18, 2024 Spotlight talk by Professor Christian Soize (Université Gustave Eiffel) on his paper “Updating Nonlinear Stochastic Dynamics of an Uncertain Nozzle Model Using Probabilistic Learning With Partial Observability and Incomplete Dataset,”

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