News & Events

We welcome the MEng students who have recently joined our group to work on research projects:
The current MEng students include:

– Dimitrije Randjelovic working on Physics-informed machine learning for fatigue and lifing—developing surrogates that predict crack-growth rate and life across diverse geometries, materials, and load spectra with embedded Paris/Walker and fracture-mechanics constraints

We are excited to have them on board and look forward to their contributions!

At the International Workshop on Structural Health Monitoring (IWSHM) 2025, Peiyuan Zhou and co-authors Jinhan Ren, James Schure, Shinan Huang, Sazedur Rahman, as well as Professors S. Mishra, J. Samuel, S. Akin and F.

Members of our group had a strong presence at the 15th International Workshop on Structural Health Monitoring (IWSHM 2025) in Stanford, CA, presenting five papers on structural health monitoring, smart metallic structures, multicopter diagnostics, acoustoelasticity, and in-situ monitoring of metal additive manufacturing processes:

At the 15th International Workshop on Structural Health Monitoring (IWSHM 2025) in Stanford, CA, our group hosted a lab booth showcasing ongoing work on intelligent metallic structures, vibration-based diagnostics, multicopter health monitoring, and in-situ sensing for metal additive manufacturing. Visitors had the opportunity to see demos, discuss our recent papers, and explore potential collaborations, further increasing the visibility of our research within the SHM community.

In May 2025 Yiming Fan successfully defended his PhD thesis in the Department of Mechanical, Aerospace, and Nuclear Engineering at Rensselaer Polytechnic Institute. Yiming Fan developed a comprehensive data-driven structural health monitoring (SHM) framework that combines deep learning, signal processing, and statistical modeling to tackle both forward and inverse damage assessment problems.