Skip to main content

Yiming Fan

Yiming
Doctoral Student

Email: fany5@rpi.edu

Education / Experience

BS: Rensselaer Polytechnic Institute (RPI)

MS: University of Michigan, Ann Arbor (UMich)

Start Date
Fall 2021
Project Title
PhD Topic: Damage State Estimation via Multi-fidelity Gaussian Process Regression Models for Active-sensing Structure Health Monitoring
PhD Topic: Explainable Machine Learning Framework for Guided Waves Signal Reconstruction and Structural Health Monitoring Under Varying Operating and Environmental States
Research Expertise & Interests

My research interests span the areas of system identification, machine learning and probabilistic models. Currently, I am focusing on multi-fidelity modeling combining data-driven and physics-based models. I am developing methodologies based on multi-fidelity Gaussian process regression models and various neural network architectures such as CAE/VAE and PINNs for state estimation. 

Bio

Yiming Fan is a third year PhD student at Rensselaer Polytechnic Institute. He is now affiliated with the Intelligent Structural Systems Laboratory (ISSL). His current research areas are related to active-sensing state estimation in SHM using probabilistic as well as ML models such as Gaussian Process Regression Models (GPRMs), Convolutional/Variational AutoEncoder (CAE/VAE) and Physics Informed Neural Networks (PINN).