Data-driven Mechanics Laboratory
College of Engineering & Applied Science
University of Colorado Boulder
Research highlights*
Assistant Professor of Engineering Science
Department of Civil, Environmental & Architectural Engineering
Department of Applied Mathematics (Affiliated Faculty)
In D2Mech Lab, we turn measured waveforms into understanding. Our objective is to build intelligent sensing-to-inference platforms for real-time monitoring and data-driven discovery of the mechanics of materials and energy systems. This includes governing equations for bulk dynamics across scales and interfacial constitutive laws. By unifying laser-based sensing, inverse scattering theory, and physics-constrained learning, we render ill-posed problems identifiable, quantify uncertainty, and rigorously connect raw signals to verified models. With those models in hand, we close the loop from data → equations/geometry → prediction → design, enabling targeted wave control, diagnostics, and robust performance predictions for materials and systems. Current applications include predictive modeling of hierarchical and particulate composites, in situ monitoring for additive manufacturing, and remote sensing of subsurface processes in unconventional energy systems.
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I joined the Civil, Environmental and Architectural Engineering Department in 2017. I am also an Affiliated Faculty of the Applied Mathematics Department as of 2019. Previously, I was a Postdoctoral Fellow and Research Assistant in the Waves & Imaging Laboratory at the University of Minnesota. I conducted my doctoral work under Bojan Guzina and Joe Labuz with the focus on next-generation imaging technologies. I completed my undergraduate and first masters degrees in Mechanical Engineering. My early research activities at Iran University of Science and Technology were focused on inverse problems in nonlinear dynamics entailing contact mechanics, experimental modal analysis, signal processing, and nonlinear vibrations.
