Research

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  UC San Diego

  Predictive real-time intelligence for metallic endurance (PRIME)

  April 2025 - Present

  • Working on a physics-based digital twin interface for uncertainty-quantified lifetime prediction of laser powder bed fusion (LPBF) parts
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  UC San Diego

  Design optimization under uncertainty for efficient powder bed fusion additive manufacturing

  September 2024 - June 2025

  • Incorporated a buffered probability of failure constraint in a design optimization problem
  • Applied the design under uncertainty framework to a metal additive manufacturing application
  • Considered both magnitude and frequency in build failures, enhanced process quality, and reduced energy consumption
• 

  UC San Diego

  Sparsity-promoting design under uncertainty for a char combustion problem

  Janurary 2024 - November 2024

  • Developed a design under uncertainty approach for a char combustion process in a limited-data setting
• 

  Vanderbilt University

  Uncertainty quantification for high-dimensional problems

  October 2019 - December 2023

  • Developed a surrogate modeling framework for problems with high-dimensional input and output
  • Developed a novel active learning strategy to adaptively improve surrogate models
  • Collaborated with Mitsubishi Heavy Industries with an application on an aircraft fuselage
  • Collaborated with NIST to apply the method to an additive manufacturing (3D printing) part
• 

  Vanderbilt University

  Intelligent mission planning using a digital twin approach

  August 2018 - December 2019

  • Conducted damage diagnosis, damage prognosis, and mission optimization with simulation and experimental data
  • Developed a probabilistic digital twin to fuse information from heterogeneous sources, account for both aleatory and epistemic uncertainties