News & Events

Our lab was represented at Materials Frontiers: Powering the Future in June 2026, a materials-focused symposium hosted by GE Vernova, through a poster presentation on physics-informed and data-driven monitoring for metal additive manufacturing.

The poster focused on melt-pool monitoring in Laser Powder Bed Fusion, combining physics-informed neural networks, statistical methods, and thermal-field reconstruction for anomaly detection and process understanding.

In March 2026, Alvin Chen succe

In November 2025, Peiyuan Zhou successfully defended his PhD thesis in the MANE Department at Rensselaer Polytechnic Institute. His research developed an advanced monitoring method that helps future aircraft structures “feel, think, and react” to damage and changing conditions. By combining smart statistical modeling, regularization, and Bayesian uncertainty quantification, his work makes vibration-based health monitoring more reliable for complex, realistic aerospace components rather than just simple lab specimens. 

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.