Associate Professor, Civil and Environmental Engineering
Matteo Pozzi is an Associate 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.
EducationPhD 2007 - University of Trento, Italy
- Bayesian methods for risk assessment and decision analysis
- Value of information
- Structural health monitoring
- Fiber optic sensors and Wireless sensing networks
- Resilient infrastructure
Memarzadeh, M., Pozzi, M., Kolter, J.Z. (2016). "Hierarchical Modeling of Systems with Similar Components: A Framework for Adaptive Monitoring and Control," Reliability Engineering & System Safety 153:159-169. (Elsevier) doi:10.1016/j.ress.2016.04.016.
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.
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.
Zonta, D., Pozzi, M. (2015). “The remarkable story of Portogruaro Civic Tower’s probabilistic health monitoring”, Structural Monitoring and Maintenance, 2(4): 301-318. (Techno Press) DOI: 10.12989/smm.2015.2.4.301.
Memarzadeh, M., Pozzi, M. "Integrated inspection scheduling and maintenance planning for infrastructure systems," Computer-Aided Civil and Infrastructure Engineering (Wiley) DOI: 10.1111/mice.12178 (pre-issued online).
Wang, P., Pozzi, M., Small, M. J., Harbert, W. (2015). "Statistical method for real-time detection of changes in seismic risk at deep-well injection sites," Bulletin of the Seismological Society of America, 105:2852-2862, doi:10.1785/0120150038.
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.
Memarzadeh, M., Pozzi, M., Kolter, J.Z. (2015). “Optimal planning and learning in uncertain environments for the management of wind farm,” ASCE Journal of Computing in Civil Engineering, 29(5), 04014076.
Ceriotti, M., Mottola, L., Picco, G.P., Murphy, A.L., Guna, S., Corrà, M., Pozzi, M., Zonta, D., Zanon, P. "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
- 2009: Best Paper Award at IPSN: Monitoring heritage buildings with wireless sensor networks: the Torre Aquila deployment