MYSP-2025-PI-002

顏王吉


下載導師簡歷CV
Section 1: Personal Particulars

顏王吉
YAN Wang-Ji
Associate Professor
853-68869548
wangjiyan@um.edu.mo
N21-5011B, University Of Macau, Macau
University of Macau
UMAC-SKL of Internet of Things for Smart City
None
https://www.fst.um.edu.mo/personal/wangji-yan/home/

Research Project provided for Macao Youth Scholars Program:

結構健康監測與力學反問題求解的概率機器學習方法研究
Research on probabilistic machine learning methods for structural health monitoring and mechanics inverse problem solving
0801 力学
0814 土木工程
Associate Professor
EASD Junior Research Award in the area of Computational Structural Dynamics, European Association of Structural Dynamics, 2023. Distinguished Young Scholar Paper Award in 13th National Conference on Random Vibration Theory and Application, 2023. Second Class of Natural Science Award of Ministry of Education of China, 2023. Second Class of Natural Science Award of Chinese Association of Vibration Engineering, 2022. The Top 2% Scientists in The World, Stanford University. Marie Skłodowska-Curie Individual Fellowship, 2018-2020. HuangShan Young Scholar Professorship, 2014-2018. Second Class of Science and Technology Progress Award of Zhejiang Province, 2017. Second Class of Science and Technology Progress Award of Chinese Highway Association, 2017. First Class of Academic Paper Contest of Anhui Province, 2016. Second Class of Natural Science Award of Anhui Province, 2015. Outstanding Young Medal for Teaching and Education, Hefei University of Technology, 2017. Arup Research Prize (Certificate of Merit), awarded by Ove Arup & Partners Hong Kong Ltd, 2012. Finalist for Best Student Paper Award, by Structural Control and Health Monitoring Committee, Engineering Mechanics Institute, ASCE, 2012.

Section 2: Research Interests and Grants

Structural Health Monitoring; Probabilistic Engineering Mechanics; Probabilistic Machine Learning; Bayesian system identification; Non-destructive testing; Physics-Informed Neural Network
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Theory and Key Technology of Distributed Parallel Intelligent Damage Diagnosis for Bridge Engineering Powered by Physical Properties of Long-gauge Strain Transmissibility, The Science and Technology Development Fund (FDCT) (0038/2024/RIB2), 1400000 MOP, PI,10/2024-09/2027.