News & Events
In September 2026, Shinan successfully passed his PhD candidacy examination in the MANE Department at Rensselaer Polytechnic Institute. His research develops data-driven health- monitoring methods for multirotor unmanned aerial vehicles that can detect, locate, and quantify propeller damage under realistic operating and flight conditions. By combining time-series modeling, statistical hypothesis testing, and Bayesian inference, his work aims to improve the reliability and safety of UAV systems while accounting for uncertainty and variability in real-world measurements.
Christos Stamopoulos has been selected to receive the Victor Peng ’81 Summer Research Project Award through Rensselaer Polytechnic Institute’s Future of Computing Institute (FOCI) for his project, “Foundation-Model Energy Landscapes: AI-Driven Bayesian Inverse Inference for Structural Dynamics and Digital Twins.”
The project addresses a growing challenge in aerospace structures, additive manufacturing, and unmanned aircraft systems: efficiently inferring latent damage, defects, and operating states from rich, multi-sensor time-series data.
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.