James H. Garrett, Jr., P.E.
Dean, College of Engineering
James H. Garrett, Jr. was appointed Dean of the College of Engineering at Carnegie Mellon University in 2013. He also holds the Thomas Lord Professorship of Civil and Environmental Engineering. Prior to becoming Dean, Garrett was Head of Carnegie Mellon’s Department of Civil and Environmental Engineering from June 2006 to December 2012. Garrett is a licensed professional engineer in Texas.
He is a founding co-director of the Smart Infrastructure Institute (formerly the Pennsylvania Smarter Infrastructure Incubator), a research center aimed at creating and evaluating sensing, data analytics and intelligent decision support for improving the construction, management and operation of infrastructure systems.
Garrett served as Co-Chief Editor of the ASCE Journal of Computing in Civil Engineering from 2008-2013. Garrett’s research and teaching interests are oriented toward applications of sensors and sensor systems to civil infrastructure condition assessment; application of data mining and machine learning techniques for infrastructure management problems in civil and environmental engineering; mobile hardware/software systems for field applications; representations and processing strategies to support the usage of engineering codes, standards, and specifications; knowledge-based decision support systems. Garrett has published over 250 journal articles, conference papers, and monograph/book chapters related to his research.
EducationPh.D. 1986 - Carnegie Mellon University
ResearchResearch Group: AIS
Research Center: Sii, CenSCIR, ICES
Areas of Interest
- Applications of sensors and sensor systems to civil infrastructure condition assessment
- Mobile hardware/software systems for field applications
- Representations and processing strategies to support the usage of engineering codes, standards, and specifications
- Knowledge-based decision support systems
E. B. Anil, B. Akinci, J. H. Garrett, O. Kurc. 2016 “Information Requirements for Earthquake Damage Assessment of Structural Walls”, Adv. Eng. Inform., Vol 30, pp. 54-64.
E. B. Anil, B. Akinci, O. Kurc, J. H. Garrett, Jr. 2015. “Building-Information-Modeling-Based Earthquake Damage Assessment for Reinforced Concrete Walls”, J. Comput. Civ. Eng.
S. Taneja, B. Akinci, J. H,. Garrett, Jr., L. Soibelman. 2016. “Algorithms for Automated Generation of Navigation Models from Building Information Models to Support Indoor Map-Matching”, Autom. Constr., Vol. 61, pp. 24-41.
S. Chen, F. Cerda, P. Rizzo, J. Bielak, J. H. Garrett, Jr. and J. Kovačević. 2014. “Semi-Supervised Multiresolution Classification Using Adaptive Graph Filtering with Application to Indirect Bridge Structural Health Monitoring”, IEEE Trans. Signal Process., 62(11), pp. 2879-2893.
Taneja, S., Akinci, B., Garrett, J., Soibelman, L., Jr., and Karimi, H. 2014. "Effects of Positioning Data Quality and Navigation Models on Map-Matching of Indoor Positioning Data." J. Comput. Civ. Eng., 04014113.
Liu, X., Akinci, B., Bergés, M., and Garrett, J., Jr. 2014. “Domain-Specific Querying Formalisms for Retrieving Information about HVAC Systems.” J. Comput. Civ. Eng., 28(1), pp. 40–49.
Gao, T., Ergan, S., Akinci, B., and Garrett, J. 2014. "Evaluation of Different Features for Matching Point Clouds to Building Information Models." J. Comput. Civ. Eng., 04014107.
Ying, Y., Garrett Jr., J. H., Oppenheim, I. J., Soibelman, L., Harley, J., Shi, J., and Jin, Y. “Towards Data-Driven Structural Health Monitoring: Application of Machine Learning and Signal Processing to Damage Detection,” Journal of Computing in Civil Engineering, Special Issue. (Invited)
Ying, Y., J. H. Garrett Jr., J. Harley, I. J. Oppenheim, J. Shi, and L. Soibelman (2012) "Damage Detection in Pipes under Changing Environmental Conditions using Embedded Piezoelectric Transducers and Pattern Recognition Techniques," Journal of Pipeline Systems Engineering and Practice, Special Issue for International Conference on Pipelines and Trenchless Technology, doi:10.1061(ASCE)PS.1949-1204.0000106.
Taneja, S., Akcamete, A., Akinci, B., Garrett Jr., J.H., Soibelman, L., East, E.W., “Analysis of three indoor localization technologies for supporting operations and maintenance field tasks”, ASCE Journal of Computing in Civil Engineering.
Shahandashti, M.S., Razavi, S.N., Soibelman, L., Berges, M., Caldas, C.H., Brilakis, I., Teizer, J., Haas, C., Garrett Jr., J.H., Akinci, B., Zhu, Z. (2011) “Data Fusion Approaches and Applications for Construction Engineering,” ASCE Journal of Construction Engineering and Management, 137(10): 863-869.
Taneja, S., Akinci, B., Garrett, J.H., Soibelman, L., Berges, M., Atasoy, G., Liu, X., Shahandashti, S.M., Anil, E.B., Ergen, E., Pradhan, A., Tang, P. (2011) “Sensing and field data capture for construction and facility operations,” ASCE Journal of Construction Engineering and Management, 137(10): 870-881.
- 2016 William Metcalf Award, Engineers’ Society of Western Pennsylvania
- 2014 Civil Engineer of the Year, American Society of Civil Engineers, Pittsburgh Section
- 2014 Recognition Award, American Society of Civil Engineers. In recognition of outstanding dedication and leadership as co-editor-in-chief of ASCE Journal of Computing in Civil Engineering
- 2012 Alexander von Humboldt Research Award
- 2010 Awarded the Thomas Lord Professorship of Civil and Environmental Engineering, Carnegie Mellon University
- 2009 Elected to ASCE Fellow Status. Fellows occupy ASCE's second-highest membership grade, and fellow status must be attained by professional accomplishments via application and election by the Membership Application Review Committee.
Dean Garrett on Smart Infrastructure for World Economic Forum
Carnegie Mellon University College of Engineering Dean Jim Garrett is among the Carnegie Mellon presenters at the World Economic Forum Ideas Lab in Tianjin, China. His presentation focuses on Smart Infrastructure, a field that is a blend of our built infrastructure, with many types of networked sensors that collect data over time and space, and sophisticated analytical techniques used to predict and visualize the conditions of that infrastructure. In other words, smart infrastructure provides the early indicators of trouble that would compel decision-makers to act in a more timely and effective manner.