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Publications & Talks

Scholarly output, conference presentations, workshops, and symposia.

Peer-Reviewed Journal Papers

  1. Elastodynamic imaging of voids in a PML-truncated layered solid using a deep convolutional neural network.

    Kim, B., Maharjan, S., Guidio, B., Thomas, J., Pranto, F. M., Schaal, C., & Jeong, C.

    Engineering Geology, 2026.

    PDF DOI: 10.1016/j.enggeo.2026.108545
    Kim, B., Maharjan, S., Guidio, B., Thomas, J., Pranto, F. M., & Jeong, C. (2026). Elastodynamic imaging of voids in a PML-truncated layered solid using a deep convolutional neural network. Engineering Geology, 108545. Engineering Geology. 
    @article{kim2026elastodynamic,
  title={Elastodynamic imaging of voids in a PML-truncated layered solid using a deep convolutional neural network},
  author={Kim, Boyoung and Maharjan, Shashwat and Guidio, Bruno and Thomas, Jacob and Pranto, Fazle Mahdi and Jeong, Chanseok},
  journal={Engineering Geology},
  pages={108545},
  year={2026},
  publisher={Elsevier}
}
  2. Convolutional neural network and level-set spectral element method for ultrasonic imaging of delamination cavities.

    Kim, B., Maharjan, S., Pranto, F. M., Guidio, B., Schaal, C., & Jeong, C.

    Ultrasonics, 2024.

    PDF DOI: 10.1016/j.ultras.2024.107254
    Kim, B., Maharjan, S., Pranto, F. M., Guidio, B., Schaal, C., & Jeong, C. (2024). Convolutional neural network and level-set spectral element method for ultrasonic imaging of delamination cavities in an anisotropic composite structure. Ultrasonics, 138, 107254. Ultrasonics. 
    @article{kim2024convolutional,
  title={Convolutional neural network and level-set spectral element method for ultrasonic imaging of delamination cavities in an anisotropic composite structure},
  author={Kim, Boyoung and Maharjan, Shashwat and Pranto, Fazle Mahdi and Guidio, Bruno and Schaal, Christoph and Jeong, Chanseok},
  journal={Ultrasonics},
  volume={138},
  pages={107254},
  year={2024},
  publisher={Elsevier}
}
  3. Convolutional neural network for identifying effective seismic force at a DRM layer for rapid reconstruction of SH ground motions.

    Maharjan, S., Guidio, B., & Jeong, C.

    Earthquake Engineering & Structural Dynamics, 2024.

    PDF DOI: 10.1002:eqe.4049
    Maharjan, S., Guidio, B., & Jeong, C. (2024). Convolutional neural network for identifying effective seismic force at a DRM layer for rapid reconstruction of SH ground motions. Earthquake Engineering & Structural Dynamics, 53(2), 894-923.. 
    @article{maharjan2024convolutional,
  title = {Convolutional neural network for identifying effective seismic force at a DRM layer for rapid reconstruction of SH ground motions},
  author = {Maharjan, S. and Guidio, B. and Jeong, C.},
  journal = {Earthquake Engineering \& Structural Dynamics},
  year = {2024},
  doi = {10.1002/eqe.4049}
}
  4. Level-Set and Learn: Convolutional Neural Network for Classification of Elements to Identify an Arbitrary Number of Voids.

    Pranto, F. M., Maharjan, S., & Jeong, C.

    Journal of Engineering Mechanics, 2023.

    PDF DOI: 10.1061:JENMDT.EMENG-6840
    Pranto, F. M., Maharjan, S., & Jeong, C. (2023). Level-Set and Learn: Convolutional Neural Network for Classification of Elements to Identify an Arbitrary Number of Voids. Journal of Engineering Mechanics. 
    @article{maharjan2024convolutional,
  title={Convolutional neural network for identifying effective seismic force at a DRM layer for rapid reconstruction of SH ground motions},
  author={Maharjan, Shashwat and Guidio, Bruno and Jeong, Chanseok},
  journal={Earthquake Engineering \& Structural Dynamics},
  volume={53},
  number={2},
  pages={894--923},
  year={2024},
  publisher={Wiley Online Library}
}
  5. Deep and Convolutional Neural Networks for Identifying Vertically Propagating Incoming Seismic Wave Motion.

    Maharjan, S., Guidio, B., Fathi, A., & Jeong, C.

    Soil Dynamics and Earthquake Engineering, 2022.

    PDF DOI: 10.1016:j.soildyn.2022.107510 Learn More
    Maharjan, S., Guidio, B., Fathi, A., & Jeong, C. (2022). Deep and Convolutional Neural Networks for identifying vertically-propagating incoming seismic wave motion into a heterogeneous, damped soil column. Soil Dynamics and Earthquake Engineering, 162, 107510. Soil Dynamics and Earthquake Engineering. 
    @article{maharjan2022deep,
  title={Deep and Convolutional Neural Networks for identifying vertically-propagating incoming seismic wave motion into a heterogeneous, damped soil column},
  author={Maharjan, Shashwat and Guidio, Bruno and Fathi, Arash and Jeong, Chanseok},
  journal={Soil Dynamics and Earthquake Engineering},
  volume={162},
  pages={107510},
  year={2022},
  publisher={Elsevier}
}

Conference Presentations

  1. Investigating Tibia Stress Fracture Using FEM.
    American Society for Bone and Mineral Research 2025, Seattle, WA.
  2. Designing Adhesive Interfaces with Superior Bond Strength: A Bioinspired Approach.
    Society for Biomaterials 2025, Chicago, IL.
  3. CNN for Identifying Effective Seismic Force at a Domain Reduction Method Layer.
    Engineering Mechanics Institute Conference 2024, Chicago, IL.
  4. Smart Bridge: Machine Learning to Identify Structural Defects in a Bridge and a Moving Vibration Source in Real-Time.
    International Mechanical Engineering Congress & Exposition 2022, Chicago, IL.
  5. Deep and CNNs for Identifying Vertically-Propagating Seismic Wave Motion.
    Engineering Mechanics Institute Conference 2022, Baltimore, MD.

Workshops & Symposia

  1. 2025 Penn Center for Musculoskeletal Disorders Annual Scientific Symposium
    University of Pennsylvania.
  2. 2025 Computational Design for Additive Manufacturing
    Newlab, NY.
  3. 2025 Finding Your Inner Modeler Workshop
    UC Irvine.
  4. 2025 AI-Powered Materials Discovery Workshop
    University of South Dakota.