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  1. ; ; ; ; ; ; ; ; ( , International Conference on Dynamic Data Driven Applications Systems)
    Free, publicly-accessible full text available November 6, 2025
  2. ; ; ; ; ; ; ; ; ; ( , SuRE Biennial ’24)
    Free, publicly-accessible full text available July 23, 2025
  3. ; ; ; ; ; ; ( , Expert Systems with Applications)
    Lin, Binshan (Ed.)
    This paper formulates a mixed integer linear programming (MILP) model to optimize a system of electric vehicle (EV) charging stations. Our methodology introduces a two-stage framework that integrates the first-stage system design problem with a second-stage control problem of the EV charging stations and develops a design and analysis of computer experiments (DACE) based system design optimization solution method. Our DACE approach generates a metamodel to predict revenue from the control problem using multivariate adaptive regression splines (MARS), fit over a binned Latin hypercube (LH) experimental design. Comparing the DACE based approach to using a commercial solver on the MILP, it yields near optimal solutions, provides interpretable profit functions, and significantly reduces computational time for practical application. 
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    Free, publicly-accessible full text available July 1, 2025
  4. ; ; ; ; ( , Mechanical systems and Signal Processing)
    Accepted Manuscript Full Text Available
  5. ; ; ; ; ( , Mechanical Systems and Signal Processing)
    Accepted Manuscript Full Text Available
  6. ; ; ( , International Conference on Medical Image Computing and Computer Assisted Intervention)
    Accepted Manuscript Full Text Available
  7. ; ; ; ( , Lecture notes in computer science (MICCAI))
    Full Text Available 
  8. ; ; ; ( , Computers in biology and medicine)
    Full Text Available 
  9. ; ; ; ( , Computers in biology and medicine)
    Accepted Manuscript Full Text Available
  10. ; ; ; ; ( , ACS Nano)