News & Events
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.
New PhD students: Petros and Christos join the lab
We are excited to welcome Petros Spiliopoulos and Christos Stamopoulos as new PhD students in our group starting in Fall 2024. Petros will be working on default detection in metal additive manufacturing, while Christos will focus on structural health monitoring, advanced stochastic methods for structural state awareness, deep learning and transformers for stochastic time series.
We look forward to their contributions to our research and teaching activities!
Ph.D. openings for Fall 2023
If you are a highly-motivated student interested in my research areas, I would be very happy to discuss funded Ph.D. research opportunities for Fall 2023.
Students with a strong background and interest in stochastic systems, system identification, structural health monitoring, and machine learning are encouraged to contact me via email.
Essential elements are the motivation and intellect of the student.