Prof. Youn​ contributed to the "Mechanical Systems and Signal Processing​ (MSSP)" Special Issue on “Physics-Informed Machine Learning Enabling Fault Feature Extraction and Robust Failure Prognosis” as a Guest Editor. This special issue is intended to include original, high-quality work that creates new theoretical foundations and models/algorithms of physics-informed machine learning for failure prognosis.​

Important Dates

February 1st, 2021: Elsevier System open for submission

December 15th, 2021: Deadline for paper submission

March 1st, 2022 or earlier: Completion of first-round reviews

May 15th, 2022 or earlier: Revised paper submission

June 20th, 2022 or earlier: Final decision notification

Guest Editors

Chao Hu, Iowa State University, US, chaohu@iastate.edu

Kai Goebel, PARC (Palo Alto Research Center), US, kgoebel@parc.com

David Howey, University of Oxford, UK, david.howey@eng.ox.ac.uk

Zhike Peng, Shanghai Jiao Tong University, China, z.peng@sjtu.edu.cn

Dong Wang, Shanghai Jiao Tong University, China, dongwang4-c@sjtu.edu.cn

Peng Wang, University of Kentucky, US, edward.wang@uky.edu

Byeng D. Youn, Seoul National University, South Korea, bdyoun@snu.ac.kr