Yingbo Zhu

Professional Experience

Teaching Experience

  • CEE 1712: Digitalization in Civil Engineering (Fall 2024), University of Pittsburgh, Pittsburgh, PA.
  • CEE 1330: Introduction to Structural Analysis (Fall 2021), University of Pittsburgh, Pittsburgh, PA.

Research Experience

Postdoc Fellow, Johns Hopkins University, Baltimore, MD (2025.03–Present)

  • Pioneering the development and optimization of smart material-based morphing structures using 4D printing technology to improve energy efficiency and functionality in advanced structural applications.
  • Innovating mesoscale phase transformation model to simulate the thermo-mechanical behavior of 4D-printed morphing structures based on shape memory polymers.

Graduate Student Research Assistant, University of Pittsburgh, Pittsburgh, PA (2021.09–2025.02)

  1. Digital twin modeling civil infrastructures

    • Developed a novel LSTM-based Multiscale Lattice Discrete Particle Model for digital twin modeling reinforced concrete structures, providing a high-fidelity method to estimate structural damage conditions.
    • Proposed a novel digital twin framework to rapidly assess the current condition of bridge structures by integrating LiDAR-Camera sensing, a high-fidelity numerical model, and a neural-network-assisted real-time response system.
    • Developed a LiDAR-RGB data fusion method to monitor the construction process of bridge structures, supporting dynamic updates of digital twin models for civil structures.

  2. Durability and sustainability of infrastructure

    • Developed a novel Coupled Lattice Discrete Particle Model to compute mass transport in concrete members subjected to long-term loading, providing critical insight into chloride invasion in stressed concrete at the mesoscopic level.
    • Developed a Physics- and Data-Based Mesoscale Modeling approach for corrosion in reinforced concrete members, enabling high-fidelity and real-time simulation of corrosion in reinforced concrete structures.

  3. Mesoscale modelling heterogeneous materials

    • Developed a Multiscale Lattice Discrete Particle Model to simulate the nonlinear response of steel–concrete composite columns subjected to cyclic loading, improving computation efficiency while maintaining prediction accuracy.
    • Developed a regularized Density-Driven Damage Mechanics Model for failure analysis of cementitious composites, offering insight into damage initiation and propagation from a density-change perspective.

Research Assistant, University of Pittsburgh, Pittsburgh, PA (2020.07–2021.08)

  • Experimentally and numerically quantified the effectiveness of CFRP in retrofitting damaged composite concrete-steel bridges, offering structural rehabilitation strategies for poor-condition infrastructure.
  • Developed a Rotating-Angle Softened Truss Model to predict the nonlinear response of CFRP-repaired damaged composite concrete-steel bridges, supporting theoretical design and optimization of rehabilitation techniques.
  • Experimentally and numerically evaluated the use of GFRP to strengthen weak regions in pultruded GFRP structures, enhancing their performance under heavy traffic loads.

Graduate Student Research Assistant, Southeast University, Nanjing, China (2017.09–2020.06)

  • Experimentally and numerically investigated the torsional response of single-box multi-cell composite box-girders with corrugated steel webs, providing insight into their structural behavior under complex loading.
  • Developed a Softened Truss Model to predict the nonlinear torsional behavior of composite concrete-steel box-girders, supporting design and optimization of advanced bridge systems.