Scheduled presentations:

• Student Prediction of Pipe-Jacking Forces Using a Physics-Constrained Neural Network
  *M. Rayner-Philipson (Ward and Burke), B. Sheil (University of Cambridge), P. Zhang (University of Cambridge)
• Student Comparative Assessment of ML Algorithms for Reference-Free Damage Detection and Localization Using FBG Sensors in Self-Referencing Configuration
  *F. Omidi Moaf (Institute of Fluid Flow Machinery, Gdansk), P. Fiborek (Institute of Fluid Flow Machinery, Gdansk), R. Soman (Institute of Fluid Flow Machinery, Gdansk)
• Student Neural calibration for hysteresis parameter estimation in bolted joint assemblies
  *E. Fuzaro de Almeida (Universidade Estadual Paulista – UNESP), R. de Oliveira Teloli (Institut FEMTO-ST – UFC, CNRS, SUPMICROTECH), S. da Silva (Universidade Estadual Paulista – UNESP)
• Damage Detection and Localization of Damage using FBG sensors in Self-Referencing Configuration
  *F. Omidi Moaf (Institute of Fluid Flow Machinery, Polish Aca), R. Soman (Institute of Fluid Flow Machinery, PAN)
• Leveraging digital twin strategy for predicting failures with limited training data
  *H. Gupta (KU Leuven), P. Kundu (KU Leuven)