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Faculty Profiles

Michael Todd

Professor, SE


Structural dynamics, nonlinear dynamics, time series modeling, structural health monitoring and prognosis digital twin strategies for civil, mechanical, and aerospace systems, fiber optic sensing, uncertainty modeling, and propagation.

Professor Todd's research applies to all structural systems—civil, mechanical, and aerospace. He focuses on developing tools drawn from dynamics, time series modeling, physical modeling, and uncertainty quantification to develop structural health monitoring and damage prognosis strategies. He also works to develop optic sensing approaches for making specialized field measurements in composite materials domains and in additively manufactured specimens. By integrating these and other sensor technologies with targeted processing algorithms, Professor Todd creates "digital twins" that continually provide information regarding health and future performance for optimal decision-making, reconfiguration, performance enhancement, and life safety. Professor Todd's unique ability to combine hardware and software research domains further strengthens the Jacobs School's position as a world leader in integrating large-scale and field testing with computational analysis for purposes of damage diagnostics, damage prognostics, and response modeling of civil, mechanical, and aerospace structural systems.

Capsule Bio:

Michael Todd joined the UC San Diego Structural Engineering Department in 2003 after a seven- year career at the U.S. Naval Research Laboratory that culminatED in his leading the Fiber Optic Smart Structures section. He has published more than 350 journal papers, conference proceedings, and reports, and holds 6 patents in the research areas described above. With partners at Los Alamos National Laboratory, Professor Todd helped create the country's first graduate degree program in structural health monitoring, damage prognosis, and validated simulations in the Jacobs School. Among his many honors, Todd received the 1999 Alan Berman NRL Publication Award, the 2003 and 2004 NRL Patent Award, the 2005 Structural Health Monitoring Person of the Year Award, and the 2021 Structural Health Monitoring Lifetime Achievement Award. He is a 2004-2005 UC San Diego Hellman Fellow and a 2005 Von Liebig Entrepreneurship award winner. He serves as the Managing Editor of the leading structural health monitoring journal, Structural Health Monitoring: An International Journal and serves on the editorial board of the Journal of Civil Structural Health Monitoring.

 

Education:

  • Ph.D., Department of Mechanical Engineering and Materials Science, Duke University, 1996
  • M.S., Department of Mechanical Engineering and Materials Science, Duke University, 1993
  • B.S.E., Department of Mechanical Engineering and Materials Science, Duke University, 1992

 

Awards:

  • Angier B. Duke Memorial Scholar 1988-1992
  • National Academy for Nuclear Training Fellow, 1990
  • Pi Tau Sigma Mechanical Engineering Honorary, 1991
  • Tau Beta Pi National Engineering Honorary, 1991
  • Phi Beta Kappa Member, 1991
  • Mechanical Engineering Faculty Award, 1992
  • National Science Foundation Graduate Fellow, 1993-1996
  • U.S. Naval Research Laboratory Alan Berman Research Publication Award, 1998.
  • U.S. Naval Research Laboratory Performance and Contribution Awards, 1998-2003
  • UCSD Hellman Faculty Fellow, 2004-2005
  • Structural Health Monitoring Person-of-the-Year Award, 2005
  • Who's Who in Engineering Education, 2005
  • Benjamin F. Meaker Visiting Fellow, University of Bristol, 2009
  • Structural Health Monitoring Lifetime Achievement Award, 2021

Selected Publications:

  • C. Jiang, M. Vega, M. Ramancha, M. D. Todd, J. P. Conte, M. Parno, and Z. Hu, “Bayesian Calibration of Multi-Level Model with Unobservable Distributed Response and Application to Miter Gates,” Mechanical Systems and Signal Processing 170(108852), 2022.
  • M. L. Funderburk, J. Tran, M. D. Todd, A. Netchaev, and K. J. Loh, “Active Scour Monitoring Using Ultrasonic Time Domain Reflectometry of Buried Slender Sensors,” Smart Materials and Structures 31(015045) 2022.
  • Y. Yang, M. Chadha, Z. Hu, and M. D. Todd, “An Optimal Sensor Placement Design Framework for Structural Health Monitoring Using Bayes Risk,” Mechanical Systems and Signal Processing 168(108618), 2022.
  • C. Jiang, M. Vega, M. D. Todd, and Z. Hu, “Model Correction and Updating of a Stochastic Degradation Model for Failure Prognosis of Miter Gates,” Reliability and Engineering System Safety 218(108203), 2022.
  • N. M. O’Dowd, A. J. Wachtor, and M. D. Todd, “Effects of Digital Fringe Projection Operational Parameters on Detecting Powder Bed Defects in Additive Manufacturing”, Additive Manufacturing 48(102454), 2021.
  • L. Colombo, M. D. Todd, C. Sbarufatti, M. Giglio, “On Statistical Multi-Objective Optimization of Sensor Networks and Optimal Detector Derivation for Structural Health Monitoring,” Mechanical Systems and Signal Processing 167(108528), 2022.
  • A. Meixedo, J. Santos, D. Ribeiro, R. Calçada, and M. D. Todd, “Online Unsupervised Detection of Structural Changes Using Train-Induced Dynamic Responses,” Mechanical Systems and Signal Processing 165(108268), 2022.
  • M. Chadha, Z. Hu, and M. D. Todd, “An Alternative Quantification of the Value of Information in Structural Health Monitoring”, Structural Health Monitoring 21(1), 138-164, 2022.
  • Y. Yang, M. Chadha, Z. Hu, M. Vega, M. Parno, and M. D. Todd, “Probabilistic Optimal Sensor Design Approach for Structural Health Monitoring Using Risk-Weighted f-Divergence,” Mechanical Systems and Signal Processing 161(107920), 2021.
  • A. Meixedo, D. Ribeiro, J. Santos, R. Calçada, and M. D. Todd, “Progressive Numerical Model Validation of a Bowstring-Arch Railway Bridge Based on Structural Health Monitoring,” Journal of Civil Structural Health Monitoring 11(2), 421-449, 2021.
  • A. Meixedo, J. Santos, D. Ribeiro, R. Calçada, and M. D. Todd, “Data-Driven Unsupervised Damage Detection in Railway Bridges Based on Traffic Induced Dynamic Responses,” Engineering Structures 238(112189), 2021.
  • R. Teloli, L. Villani, S. da Silva, and M. D. Todd, “On the Use of the GP-NARX Model for Predicting Hysteresis Effects of Bolted Joint Structures,” Mechanical Systems and Signal Processing 159(107751), 2021.
  • J.-S. Pei, F. Gay-Balmaz, D. J. Luscher, M. D. Todd, J. L. Beck, J. P. Wright, Y. Qiao, M. B. Quadrelli, C. R. Farrar, and N. A. J. Lieven, “Connecting Mem-Models with Classical Theories,” Nonlinear Dynamics 103(2), 1321-1344, 2021.
  • D. Ribiero, J. Leite, A. Meixedo, N. Pinto, R. Calçada, and M. D. Todd, “Statistical Methodologies for Removing the Operational Effects on the Dynamic Response of a High-rise Telecommunications Tower,” Structural Control and Health Monitoring 28(4), e2700(25 pp), 2021.
  • M. A. Vega, Z. Hu, T. B. Fillmore, M. D. Smith, and M. D. Todd, “A Novel Framework for Integration of Abstracted Inspection Data and Structural Health Monitoring for Damage Prognosis of Miter Gates, Reliability Engineering and System Safety 211 (107561), 2021.
  • Z. Wu, S. Chong, and M. D. Todd, “Laser Ultrasonic Imaging of Wavefield Spatial Gradients for Damage Detection,” Structural Health Monitoring 20(3), 960-977, 2021.
  • M. Vega and M. D. Todd, “A Variational Bayesian Neural Network for Structural Health Monitoring and Cost-Informed Decision-Making in Miter Gates,” Structural Health Monitoring 21(1), 4-18, 2022.
  • M. Chadha and M. D. Todd, “Poisson Bracket Formulation of a Higher-Order, Geometrically-Exact Beam,” Applied Mathematics Letters 113 (106842), 2021.
  • N. M. O’Dowd, A. Wachtor, and M. D. Todd, “A Probability Density Function Model Describing Height Estimation Uncertainty Due to Image Pixel Intensity Noise in Digital Fringe Projection Measurements,” Optics and Lasers in Engineering, Optics and Lasers in Engineering 138 (106422), March 2021.
  • S. Chong and M. D. Todd, “Spatial Ultrasonic Wavefront Characterization Using a Laser Parametric Curve Scanning Method, Ultrasonics 110 (106242), 2021.
  • N. M. O’Dowd, R. Madarshahian, M. Leung, J. Corcoran, and M. D. Todd, “A Bayesian Implementation of the Failure Forecast Method for Fatigue Prediction,” International Journal of Fatigue 142 (105943), 2021.
  • L. Villani, S. da Silva, A. Cunha, and M. D. Todd, “On the Detection of a Nonlinear Damage in an Uncertain Beam Using Stochastic Volterra Series,” Structural Health Monitoring 19(4), 1137-1150, 2020.
  • M. Chadha and M. D. Todd, “The Mathematical Theory of a Higher-Order, Geometrically-Exact Beam with a Deforming Cross-Section,” International Journal of Solids and Structures 202, 854-880, 2020.
  • M. Vega, Z. Hu, and M. D. Todd, “Optimal Maintenance Decisions for Deteriorating Quoin Blocks in Miter Gates Subject to Uncertainty in the Condition Rating Protocol,” Reliability Engineering and System Safety, 204 (107147), 2020.
  • N. M. O’Dowd, A. Wachtor, and M. D. Todd, “A Model for Describing Phase-Converted Intensity Image Intensity Noise in Digital Fringe Projection Techniques,” Optics and Lasers in Engineering 134 (106293), November 2020.
  • H. Wan, W. Ren, and M. D. Todd, “Arbitrary Polynomial Chaos Expansion Method for Uncertainty Quantification and Global Sensitivity Analysis in Structural Dynamics,” Mechanical Systems and Signal Processing 142 (106732), 2020.
  • F. Gharibnezhad, L. Mujica, J. Rodellar, and M. D. Todd, “Considering Temperature Effects on Robust PCA Orthogonal Distance as a Damage Detector,” Structural Health Monitoring 19(3), 781-795, 2020.
  • M. Chadha and M. D. Todd, “On the Derivatives of Curvature of Framed Space Curve and Their Time-updating Scheme, Applied Mathematics Letters 99 (105989), 2020.

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Email:
mdtodd@ucsd.edu

Office Phone:
858-534-5951

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