一、个人简介

2024年3月毕业于香港理工大学土木工程系，博士学位。主要研究方向为基于深度学习的非线性建模与时序信号重构等。

姓 名：叶昕

毕业院校：香港理工大学

学习经历：浙江大学（本科），香港理工大学（博士）

职称：讲师

研究方向：结构振动控制、机器学习、深度学习

二、代表论著

1、Ye X, Ni Y Q, Sajjadi M, et al. Physics-guided, data-refined modeling of granular material-filled particle dampers by deep transfer learning[J]. Mechanical Systems and Signal Processing, 2022, 180: 109437.

2、Ye X, Ni Y Q, Ao W K, et al. Modeling of the hysteretic behavior of nonlinear particle damping by Fourier neural network with transfer learning[J]. Mechanical Systems and Signal Processing, 2024, 208: 111006.

3、Li G Z, Ye X, Deng E, et al. Aerodynamic mechanism of a combined buffer hood for mitigating micro-pressure waves at the 400 km/h high-speed railway tunnel portal[J]. Physics of Fluids, 2023, 35(12).

4、Tan Y K, Wang Y L, Deng E, et al. Automatic damage detection and data completion for operational bridge safety using convolutional echo state networks[J]. Automation in Construction, 2024, 166: 105606.

三、联系方式

电子邮箱：[email protected]