Dr. Thomas Matarazzo, Ph.D. Assistant Professor Associate Director of High-Performance Computing, Center for Innovation and Engineering firstname.lastname@example.org Biography Dr. Thomas Matarazzo received a B.S. degree (summa cum laude) in civil engineering from Manhattan College and M.S. and Ph.D. degrees in structural engineering from Lehigh University. His research specializes in monitoring and intelligence systems for civil and urban infrastructure, mobile sensor networks, autonomous sensing platforms, and multipurpose sensor data and urban services. In 2015 and 2016 he was an NSF East Asia and Pacific Summer Institutes research fellow, then postdoc at the Nakashima-Kurata Laboratory in the Disaster Prevention Research Institute at Kyoto University, Japan. He joined the MIT Senseable City Lab as a postdoctoral researcher in 2016 where he led a multidisciplinary research team, in collaboration with industry and several government entities, to better understand how crowdsourced smartphone data from vehicle trips can support bridge maintenance. He also has postdoctoral research experience with the Department of Information Science at Cornell Tech. In Spring 2020, he was an Adjunct Assistant Professor at Columbia University, where he taught a new course “Data Science Methods for Urban Systems” in the Graduate School of Architecture, Planning and Preservation. He is a recipient of several awards, such as the Microsoft AI for Earth Award (2018). Ongoing Research Projects Modal Identification of Bridges based on Crowdsourced Smartphone Data Structural Modal Identification of the Bear Mountain Bridge Applications of Structural Damage Detection for Aircraft Components Vehicular Sensor Networks and Autonomous Infrastructure Sensing Publications & Presentations Selected Peer-reviewed Technical Publications: Eshkevari, S., Matarazzo, T.J., & Pakzad, S.N. (2020). “Simplified Vehicle-Bridge Interaction for Medium- to Long-span Bridges Subject to Random Traffic Load”, Journal of Civil Structural Health Monitoring. 10, 693–707 Eshkevari, S., Matarazzo, T.J., & Pakzad, S.N. (2020). “Bridge Modal Identification using Acceleration Measurements within Moving Vehicles”, (Elsevier) Mechanical Systems & Signal Processing, 141, 106733 Eshkevari, S., Pakzad, S.N., Takac, M., & Matarazzo, T.J., (2019). “Modal Identification of a Bridge with Sparse Vibration Data”, (ASCE) Journal of Engineering Mechanics. DOI: 10.1061/ (ASCE)EM.1943-7889.0001733 Anjomshoaa, A., Duarte, F., Rennings, D., Matarazzo, T.J., Schmitt, P., DeSouza, P., & Ratti, C. (2018). “City Scanner: Building and Scheduling a Mobile Sensing Platform for Smart City Services”, IEEE Internet of Things Journal. DOI: 10.1109/JIOT.2018.2839058 Matarazzo, T.J., Santi, P., Pakzad, S.N., Carter, K., Ratti, C., Moaveni, B., Osgood, C., & Jacob, N. (2018). “Crowdsensing Framework for Monitoring Bridge Vibrations Using Moving Smartphones”, Proceedings of the IEEE (Smart Cities Special Issue). DOI: 10.1109/JPROC 2018.2808759 Matarazzo, T.J., Kurata, M., Nishino, H., & Suzuki, A. (2017). “Post-earthquake Strength Evaluation of Steel Moment-Resisting Frame with Multiple Beam-column Fractures using Local Monitoring Data”, (ASCE) Journal of Structural Engineering. 04017217 Matarazzo, T.J. & Pakzad, S.N. (2017). “Scalable Structural Modal Identification using Dynamic Sensor Network Data with STRIDEX”, Computer-Aided Civil and Infrastructure Engineering (Special issue on Innovations in SHM). DOI 10.1111/mice.12298 Matarazzo, T.J. & Pakzad, S.N. (2016). “Truncated Physical Model for Dynamic Sensor Networks with Applications in High-Resolution Mobile Sensing and BIGDATA”, (ASCE) Journal of Engineering Mechanics, 04016019. Matarazzo, T.J. & Pakzad, S.N. (2016). “Structural Identification for Mobile Sensing with Missing Observations”, (ASCE) Journal of Engineering Mechanics, 04016021 Matarazzo, T.J. & Pakzad, S.N. (2016). “STRIDE for Structural Identification using Expectation Maximization: Iterative Output-Only Method for Modal Identification”, (ASCE) Journal of Engineering Mechanics, 04015109. Matarazzo, T.J. & Pakzad, S.N. (2015). “Sensitivity Metrics for Maximum Likelihood Modal Identification”, (ASCE-ASME) Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering (Invited article in Special Issue on Uncertainty Quantification and Propagation in Structural Systems), B4015002. Selected Invited Lectures and Featured Presentations: “Digital Infrastructure and Cooperative Computation in Smart and Resilient Cities”, 27 Feb. 2020, School of Architecture, Civil and Environmental Engineering Seminar, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. “Senseable Cities: exploring the intersection of physical and digital space”, 10 Oct. 2019, 8th United Nations World Tourism Organization Global Summit, Nur-Sultan, Kazakhstan. “Data-driven Infrastructure Informatics in Intelligent and Resilient Cities”, 1 May 2019, Civil Engineering Seminar, Cornell University, NY USA. “Senseable Cities: exploring the intersection of physical and digital space”, 26 Oct. 2018, H. Campbell and Eleanor R. Stuckeman School of Architecture and Landscape Architecture, The Pennsylvania State University, State College, PA USA. “Senseable Cities: exploring the intersection of physical and digital space”, 25 Oct. 2018, Materials Day Smart Cities Panel Session, The Pennsylvania State University, State College, PA USA. “Data-driven Infrastructure Informatics in Smart and Resilient Cities”, 26 Jan. 2018, Mechanical and Civil Engineering Seminar, California Institute of Technology, Pasadena, CA USA. “Data-driven Infrastructure Informatics in a Smart City”, 4 Dec. 2017, Research Seminar, Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, New Zealand.