Weifei Hu received the B.S. degree in 2008 from Zhejiang University, Hangzhou, China, the M.S. degree in 2010 from Hanyang University, Seoul, South Korea, and the Ph.D. degree in 2015 from the University of Iowa, Iowa city, Iowa, USA, all in mechanical engineering. From February 2016 to September 2018, Dr. Hu was a postdoctoral fellow at Cornell University, Ithaca, New York, USA. He is currently holding a tenured Associate Professor position at the School of Mechanical Engineering, Zhejiang University.  His research interests include Digital Twin, Artificial Intelligence, Design Under Uncertainty, and Wind Energy. His work has been published in over 100 peer-reviewed journals and conference proceedings, e.g., Journal of Mechanical Design, Mechanical Systems and Signal Processing, Structural and Multidisciplinary Optimization, Journal of Intelligent Manufacturing, Journal of Manufacturing Systems, Renewable and Sustainable Energy Reviews, Applied Energy, Renewable Energy, Wind Energy. He has published 2 Springer books in wind energy and design optimization under uncertainty, respectively, and is holding >20 patents. He has been selected in the Stanford/Elsevier’s Top 2% Scientist Rankings in Mechanical Engineering field. His work on reliability-based design of large-scale offshore wind turbines considering multi-source uncertainties received the second prize of Zhejiang Province Science and Technology Progress Award in November 2024. His work on digital twin of underground engineering equipment under complex working condition received the silver award of the 48th Geneva International Exhibition of Inventions in April 2023. He is now serving as an associate editor for the journal Wind Energy Science, an editorial board member for the journal Wind Energy, and a review editor for the journal Structural and Multidisciplinary Optimization, as well as serving many international conferences as chairs/co-chairs/organizers (e.g., the Asian Congress of Structural and Multidisciplinary Optimization (ACSMO) and the World Congress of Structural and Multidisciplinary Optimization (WCSMO)).