Regular biography
Michael D. Todd is a Distinguished Professor and Department Chair in the Structural Engineering Department at the University of California, San Diego. His research focuses on structural dynamics, nonlinear dynamics, time series modeling, structural health monitoring, and digital twin strategies for civil, mechanical, and aerospace systems. He develops tools for structural health monitoring and damage prognosis using dynamics, uncertainty quantification, and fiber optic sensing. Todd's work integrates sensor technologies with processing algorithms to create digital twins for optimal decision-making and life safety. He has published over 350 papers and holds 6 patents in these areas. Todd has also contributed to creating the first graduate degree program in structural health monitoring at UC San Diego.
Scholar-generated biography
Michael Todd is a Professor of Structural Engineering at the University of California San Diego, specializing in structural health monitoring, time series analysis, mechanics, and nonlinear dynamics. His research focuses on developing advanced sensor technologies and data-driven methodologies for structural health monitoring, including energy harvesting, wireless sensor networks, and Bayesian approaches for optimal sensor placement. He also explores nonlinear dynamics and chaos theory for damage detection and vibration-based assessment. His work integrates fiber Bragg grating sensors, interferometric demodulation, and digital twin technologies to enhance structural reliability and performance. Key contributions include damage detection in railway bridges, isogeometric fatigue prediction, and variational Bayesian neural networks for decision-making in structural systems.