Publications

Publications

Full publications can be found in my Google Scholar profile (link).

 

Published or Accepted:

  1. Minhee Kim* (2024), “Iterative Durability Design of Products via Degradation-Informed Bayesian Optimization”, to be published in IEEE Transactions on Automation Science and Engineering
  2. Ye Kwon Huh, Minhee Kim*, Kaibo Liu, and Shiyu Zhou (2024), “An Integrated Uncertainty Quantification Model for Longitudinal and Time-to-event Data”, to be published in IEEE Transactions on Automation Science and Engineering
  3. Ye Kwon Huh, Minhee Kim*, Katie Olivas, Todd Allen and Kaibo Liu (2024), “Degradation Modeling using Bayesian Hierarchical Piecewise Linear Models: A case study to predict void swelling in irradiated materials”, to be published in Journal of Quality Technology
  4. Minhee Kim, Todd Allen and Kaibo Liu* (2023), “Covariate-dependent Sparse Data Analysis,” INFORMS Journal on Data Science, 2 (1), 81-98.
    • Selected for presentation in the Natrella invited session in 2021 Quality & Productivity Research Conference (QPRC)
  5. Elisa Ou, Minhee Kim, Todd Allen, and Kaibo Liu* (2022), “Automatic Recognition System for Document Digitization in Nuclear Power Plants”, Nuclear Engineering and Design, 398, 111975.
  6. Minhee Kim, Changyue Song, and Kaibo Liu* (2022), “Individualized Degradation Modeling and Prognostics in a Heterogeneous Group via Incorporating Static Covariate Information,” IEEE Transactions on Automation Science and Engineering, 19 (3), 2074-2094.
  7. Minhee Kim, Jing-Ru C. Cheng, and Kaibo Liu* (2021), “An Adaptive Sensor Selection Framework for Multisensor Prognostics,” Journal of Quality Technology, 53 (5), 566-585.
  8. Zhan Ma, Shu Wang, Minhee Kim, Kaibo Liu, Chun-Long Chen, and Wenxiao Pan* (2021), “Transfer learning of memory kernels for transferable coarse-graining of polymer dynamics,” Soft Matter, 17, 5864-5877.
    • Featured on the front cover of Soft Matter
  9. Minhee Kim and Kaibo Liu* (2020), “A Bayesian Deep Learning Framework for Interval Estimation of Remaining Useful Life in Complex Systems by Incorporating General Degradation Characteristics,” IISE Transactions, 53(3), 326-340.
    • Received the Best Student Poster Competition (Honorable mention) in the Quality, Statistics and Reliability Section of 2020 INFORMS Annual Meeting
    • Selected for presentation in the IISE Transactions invited session in 2021 INFORMS Annual Meeting
    • Selected as a feature article in ISE Magazine
  10. Minhee Kim, Elisa Ou, Po-Ling Loh, Todd Allen, Robert Agasie, and Kaibo Liu* (2020), “RNN-Based Online Anomaly Detection in Nuclear Reactors for Highly Imbalanced Datasets with Uncertainty,” Nuclear Engineering and Design, 364, 110699.
    • Received the Best Student Paper Award (2nd place) in the Energy Systems Section of 2021 Industrial and Systems Engineering Research Conference (ISERC)
  11. Minhee Kim, Changyue Song, and Kaibo Liu* (2019), “A Generic Health Index Approach for Multisensor Degradation Modeling and Sensor Selection,” IEEE Transactions on Automation Science and Engineering, 16(3), 1426-1437.
    • Selected for presentation in the IEEE T-ASE invited session in 2019 INFORMS Annual Meeting
  12. Chang Hyup Oh, Minhee Kim, Byung-In Kim, and Young Myoung Ko* (2019), “An Efficient Building Evacuation Algorithm in Congested Networks,” IEEE Access, 7, 169480-169494.

Under review or In preparation:

  1. Zihan Li, Akash Deep, Jaesung Lee and Minhee Kim*, “A New View of Neural Network-based Health Index: Connecting Prediction and Operational Decision-Making to Address Underspecification,” in preparation