Curriculum Vitae

Education:

Research Interests:

• Structural health monitoring (SHM), vibration-based damage detection and prognosis
• Infrastructure resilience and sustainability, intelligent infrastructures and smart city
• Uncertainty quantification in SHM
• Time series modeling and signal processing
  
• Ultrasonic guided wave testing and non-destructive evaluation (NDE)
• Surrogate modeling of complex systems, online model updating
• Machine learning and Bayesian inference regarding SHM decision-makings
• Data mining for infrastructural systems
• Cyber-physical systems, haptics and human machine interaction
  
  
  

Professional Experiences:

Journal Publications:

• H. P. Wan, Z. Mao, M. D. Todd, W. X. Ren, Gaussian Process Model: Application to Analytical Contribution Quantification of Individual Uncertain Parameters in Structural Dynamics, under review in Journal of Sound and Vibration
• X. Y. Zhao, Z. Q. Lang, G. Park, C. R. Farrar, M. D. Todd, Z. Mao, K. Worden, A New Transmissibility Analysis Method for Detection and Location of Damage with Nonlinear Features in MDOF Structural Systems, in press in IEEE/ASME Transactions on Mechatronics (digital copy available online)
• G. Liu, Z. Mao, M. D. Todd and Z. Huang, Localization of nonlinear damage using state-space-based predictions under stochastic excitation, Smart Materials and Structures, Volume 23(2), (2014) 025036
• H. P. Wan, Z. Mao, M. D. Todd, W. X. Ren, Analytical Uncertainty Quantification for Modal Frequencies with Structural Parameter Uncertainty Using a Gaussian Process Metamodel, Engineering Structures, Volume 75, p.577-589 (2014)
• G. Liu, Z. Mao, M. D. Todd and Z. Huang, Damage Assessment with State-Space Embedding Strategy and Singular Value Decomposition under Stochastic Excitation, Structural Health Monitoring : An International Journal, Structural Health Monitoring, Vol. 13(2) 131–142 (2014)
• Z. Mao and M. D. Todd, Statistical modeling of frequency response function estimation for uncertainty quantification, Mechanical Systems and Signal Processing, Volume 38, p.333-345. (2013)
• Z. Mao and M. D. Todd, Optimal Structural Health Monitoring Feature Selection via Minimized Performance Uncertainty, Key Engineering Materials, Vol. 558, p.235-243. (2013)
• Z. Mao and M. D. Todd, A model for quantifying uncertainty in the estimation of noise-contaminated measurements of transmissibility, Mechanical Systems and Signal Processing, Volume 28, p. 470-481. (2012)
• Z.Q. Lang, G. Park, C.R. Farrar, M.D. Todd, Z. Mao, L. Zhao, K. Worden, Transmissibility of non-linear output frequency response functions with application in detection and location of damage in MDOF structural systems, International Journal of Non-Linear Mechanics, Volume 46, Issue 6, Pages 841-853, (2011)
• Z. Mao, L. Gui and Z. Fan, Research and development of free-fall drop tower impact facility, Experimental Technology and Management, Vol. 20. No.5. P22-29, (2003) in Chinese

Conference Proceedings:

• Z. Mao and M. D. Todd, Comparison of Damage Classification between Recursive Bayesian Model Selection and Support Vector Machine, to be appeared in the Proceedings of the Society for Experimental Mechanics Series (IMAC 2015)
• M. D. Todd, Z. Mao and D. Mascarenas, Investigation of an “Echo-Location” Approach for Damage Detection in Aerospace Structures, the Proceedings of the Second Advances in Structural Health Management and Composite Structures (ASHMCS 2014)
• Z. Mao and M. D. Todd , Structural Damage Classification Comparison using Support Vector Machine and Bayesian Model Selection, the Proceedings of the Seventh European Workshop on Structural health Monitoring (EWSHM 2014)
• Z. Mao and M. D. Todd , Uncertainty Quantification of Damage Detection Features Derived from Frequency Response Models, the Proceedings of the Fourth International Symposium on Life-Cycle Civil Engineering (IALCCE 2014)
• Z. Mao and M. D. Todd, A Bayesian Damage Prognosis Approach Applied to Bearing Failure, Topics in Model Validation and Uncertainty Quantification, Proceedings of the Society for Experimental Mechanics Series, Vol. 4 (IMAC 2014)
• Z. Mao and M. D. Todd, Bayesian Updating of Detection Capability with Frequency Response Function Related Structural Health Monitoring Features, the Proceedings of the 9th International Workshop on Structural Health Monitoring (IWSHM 2013)
• Z. Mao and M. D. Todd, Uncertainty Modeling and Quantification for Structural Health Monitoring Features Derived from Frequency Response Estimation, the 10th International Conference on Damage Assessment of Structures (DAMAS 2013)
• Z. Mao and M. D. Todd, A Bayesian Framework of Transmissibility Model Selection and Updating, Proceedings of the Society for Experimental Mechanics Series, Volume 6, 621-626, (IMAC 2013)
• Z. Mao and M. D. Todd, Frequency response feature selection in a Bayesian framework, Proceedings of SPIE 8695, 869535 (SPIE Smart Structures/NDE 2013)
• Z. Huang, G. Liu, M. D. Todd and Z. Mao, Damage detection using vector auto-regressive models, Proceedings of SPIE 8695, 86953E (SPIE Smart Structures/NDE 2013)
• Z. Mao and M. D. Todd, Optimal Structural Health Monitoring Feature Selection via Minimized Performance Uncertainty, Proceedings of the Asia Pacific Workshop on Structural Health Monitoring (APWSHM2012)
• Z. Mao and M. D. Todd, The quantification of uncertainty in SHM features derived from frequency response estimation, to appear in Proceedings of the ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS 2012)
• Z. Mao and M. D. Todd, Uncertainty propagation of transmissibility-based structural health monitoring features, Proceedings of SPIE 8348, 834811 (SPIE Smart Structures/NDE 2012)
• Z. Mao and M. D. Todd, Rapid Structural Condition Assessment Using Transmissibilities with Quantified Confidence for Decision Making, Proceedings of the Society for Experimental Mechanics Series, Volume 29, 133-140, (IMAC 2012)
• Z. Mao and M. D. Todd, Uncertainty Quantification in Transmissibility-Derived Features Used for Fault Detection, Proceedings of the 8th International Workshop on Structural Health Monitoring (IWSHM 2011)
• Z. Mao and M. D. Todd, Statistical quantification of the uncertainty in transmissibility feature for structural condition binary classification, Proceedings of SPIE 7984, 79842H (SPIE Smart Structures/NDE 2011)
• Z. Mao and M. D. Todd, A Model of Uncertainty Quantification in the Estimation of Noise-Contaminated Transmissibility Measurements for System Identification, Proceedings of the Society for Experimental Mechanics Series, Volume8, 389-398, (IMAC 2011)
• Z. Mao and M. D. Todd, A structural transmissibility measurements-based approach for system damage detection, Proceedings of SPIE 7650, 76500G (SPIE Smart Structures/NDE 2010)
• Z. Mao and M. D. Todd, Comparison of shape reconstruction strategies in a complex flexible structure, Proceedings of SPIE 6932, 69320H (SPIE Smart Structures/NDE 2008)

Invited Talks:

• Uncertainty Quantification Enhanced Structural Health Monitoring Decision-Making for Infrastructure Sustainability, Department of Mechanical and Aerospace Engineering, Monash University, Australia (October 2014)
• Uncertainty Quantification Enhanced Decision-Making for Structural Sustainability - from Frequentist to Bayesian, Department of Civil and Environmental Engineering, Pennsylvania State University (February 2014)
• Uncertainty Involved Damage Diagnosis and Prognosis Decision-Making Procedure, Collaborative Innovation Center for High-End Manufacturing Equipment, Xi'an Jiaotong University, China, (December 2013)
• Structural Damage Identification under Uncertainty, from Frequentist to Bayesian, College of Civil Engineering, Chongqing University, China, (December 2013)
• A Supervised-Learning Approach for Damage Classification and Prognosis, Department of Mechanical Engineering, Tsinghua University, China, (December 2013)
• A Bayesian Experimental Design Approach for Optimization and Uncertainty Quantification in Aerospace Structural Modeling and Analysis, U.S. Air Force Office of Scientific Research (AFOSR) Structural Mechanics Annual Grantees Meeting, Arlington, VA (July 2013)
• Uncertainty Quantification Enhanced Structural Health Monitoring Capability and a Bayesian Thrust, School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, China, (September 2012)
• Uncertainty Quantification in Structural Health Monitoring features for an Enhanced Decision-Making Capability, School of Mechanical Engineering, Xi'an Jiaotong University, China, (August 2012)
• Uncertainty Quantification in Vibration-Based Structural Health Monitoring for Enhanced Decision-Making Capability, SE290 Seminar Series, Department of Structural Engineering, University of California, San Diego, (May 2012)

Poster Presentations:

• Z. Mao and M. D. Todd, Uncertainty Quantification for Enhanced Structural Health Monitoring and Damage Prognosis, Postdoctoral Research Symposium, University of California, San Diego (2013)
• Z. Mao and M. D. Todd, Enhanced Structural Health Monitoring Capability With Quantified Uncertainties - a Bayesian Approach, U.S. Air Force Office of Scientific Research Grantees Meeting, Arlington, VA (2012)
• Z. Mao and M. D. Todd, Uncertainty quantification in transmissibility-derived features used for faulty detection, Research Expo of Jacobs School of Engineering, University of California, San Diego (2012)
• Z. Mao and M. D. Todd, Statistical quantification of the uncertainty in transmissibility feature for structural condition binary classification, Research Expo of Jacobs School of Engineering, University of California, San Diego (2011)
• Z. Mao and M. D. Todd, A Structural Transmissibility Measurements-Based Approach for System Damage Detection, Research Expo of Jacobs School of Engineering, University of California, San Diego (2010)
• Z. Mao and M. D. Todd, Comparison of Shape Reconstruction Strategies in a Complex Flexible Structure, Research Expo of Jacobs School of Engineering, University of California, San Diego (2008)

Technical Reports:

• M. D. Todd and Z. Mao, A Bayesian Experimental Design Approach For Optimization And Uncertainty Quantification In Aerospace Structural Modeling And Analysis, to: U.S. Air Force Office of Scientific Research (Grant Number FA9550-10-1-0455, Sep 2010-Sep 2013)
• M. D. Todd and Z. Mao, A Trained Network Solution for Multistate Structural Awareness, to: U.S. Air Force Research Laboratory, Space Vehicles Directorate (AFRL/RVSV), AFRL-RV-PS- PSTR-2011-0172 (2012)

Patent:

• Chinese Patent: A kind of hook with the function of releasing, ZL-02-1-48869.X (B66C 1/26), issued on December 7 2005