Carnegie Mellon University

Matteo Pozzi

Matteo Pozzi

Professor, Civil and Environmental Engineering

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Address
Civil & Environmental Engineering
Carnegie Mellon University
Pittsburgh, PA 15213-3890

Bio

Matteo Pozzi is a Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University. His research focuses on probabilistic risk analysis and decision optimization applied to civil infrastructures, integrating fiber optic sensors, and using wireless sensors to measure strain and vibrations.

Pozzi looks at methods to reliably mitigate risks and extend systems life-spans in civil systems. The analysis of this data and integrated reliability assessment tools can help stakeholders in their decision making processes towards a more sustainable use of resources.

His group is focused on probabilistic models for seismic vulnerability, deterioration, optimal planning for mitigation of extreme events, maintenance and inspection scheduling. Using a computational approach, based on probabilistic graphical models, his research allows for integrated modeling of large heterogeneous systems through extensive use of simulations and analytical approximations.

Education

PhD 2007 - University of Trento, Italy

Research

Research Group: IESS, MCM, CREST

  • Bayesian methods for risk assessment and decision analysis
  • Value of information
  • Structural health monitoring
  • Fiber optic sensors and Wireless sensing networks
  • Resilient infrastructure

Publications

Pozzi, M., Malings C., Minca A., (2020). "Information avoidance and overvaluation under epistemic constraints: principles and implications for regulatory policies," Reliability Engineering & System Safety, 197:106814 (Elsevier) doi.org/10.1016/j.ress.2020.106814.

Memarzadeh, M., Pozzi, M., (2019). "Model-free reinforcement learning with model-based safe exploration: Modeling adaptive recovery process of infrastructure systems," Structural Safety, 80:46-55 (Elsevier) doi.org/10.1016/j.strusafe.2019.04.003.

Li, S., Pozzi, M., (2019). "What Makes Long-term Monitoring Convenient? A Parametric Analysis of Value of Information in Infrastructure Maintenance," Structural Control and Health Monitoring, 26(5):e2329 (Wiley) doi.org/10.1002/stc.2329.

Velibeyoglu, I., Noh, H.Y., Pozzi, M., (2019). "A graphical approach to assess the detectability of multiple simultaneous faults in air handling units," Energy and Buildings, 184:275-288 (Elsevier) doi.org/10.1016/j.enbuild.2018.12.008.

Malings, C., Pozzi, M., Klima, K., Bergés, M., Bou-Zeid, E., Ramamurthy, P., (2018). "Surface Heat Assessment for Developed Environments: Optimizing Urban Temperature Monitoring," Building and Environment, 141:143-154 (Elsevier) doi.org/10.1016/j.buildenv.2018.05.059.

Memarzadeh, M., Pozzi, M., (2016). "Value of Information in Sequential Decision Making: component inspection, permanent monitoring and system-level scheduling," Reliability Engineering & System Safety, 154:137-151. (Elsevier) doi:10.1016/j.ress.2016.05.014.

Tien, C., Pozzi, M., Der Kiureghian, A., (2016). "Probabilistic framework for assessing maximum structural response based on sensor measurements," Structural Safety, 61:43-56. (Elsevier) doi:10.1016/j.strusafe.2016.03.003.

Wang, P., Small, M.J., Harbert, W., Pozzi, M., (2016). "A Bayesian approach for assessing seismic transitions associated with wastewater injections," Bulletin of the Seismological Society of America, 106:832-845 (SSA) doi:10.1785/0120150200.

Malings, C., Pozzi, M. (2016). "Conditional entropy and value of information metrics for optimal sensing in infrastructure systems," Structural Safety, 60:77-90. (Elsevier) doi:10.1016/j.strusafe.2015.10.003.

Pozzi, M., Der Kiureghian, A. (2015). "Response spectrum analysis for floor acceleration," Earthquake Engineering & Structural Dynamics, 44(12):2111–2127 | DOI: 10.1002/eqe.2583.

Ceriotti, M., Mottola, L., Picco, G.P., Murphy, A.L., Guna, S., Corrà, M., Pozzi, M., Zonta, D., Zanon, P. (2009).  "Monitoring heritage buildings with wireless sensor networks: the Torre Aquila deployment". Proceedings of the 8th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2009, SPOTS track), San Francisco, CA, April 13-16, 2009

Recent Awards 

  • 2017: CAREER Award - National Science Foundation. Infrastructure Management under Model Uncertainty: Adaptive Sequential Learning and Decision Making
  • 2009: Best Paper Award at IPSN: Monitoring heritage buildings with wireless sensor networks: the Torre Aquila deployment

Courses

  • 12-421 Engineering Economics
  • 12-704 Probability and Estimation Methods for Engineering Systems
  • 12-735 Urban Systems Modeling

Matteo Pozzi: Risk Analysis & Decision Making: Civil Infrastructure Systems

Matteo Pozzi, Assistant Professor of Civil and Environmental Engineering, uses micro air vehicles to decide how best to maintain wind farms and other civil infrastructure systems over time.