Experience

Sep 2025 – present
Lemont, IL
Argonne National Laboratory Assistant Computational Scientist

  • Develop imaging registration algorithms for visible light microscopy, XRF, and tomography.
  • Research on AI and foundation models for X-ray science applications.
  • Collaborate with beamline scientists to develop autonomous experimentation and data analysis tools.

Oct 2023 – Sep 2025
Lemont, IL
Argonne National Laboratory Postdoctoral Appointee

  • Developed advanced computational imaging algorithms for XRF, ptychography, and tomography.
  • Supported research on automated parameter tuning and data analysis using AI techniques.
  • Collaborated with beamline scientists on data processing and analysis for APS user experiments.

May 2022 – Aug 2022
Los Altos, CA
Toyota Research Institute Research Intern

  • Developed a reinforcement learning framework for dopant design in catalyst materials.
  • Analyzed experimental data, developed predictive models, and performed explainability studies.

Jul 2017 – Sep 2017
Vancouver, BC
University of British Columbia MITACS Globalink Research Intern

  • Developed a biomass combustion PDE model and carried out simulation.

Education

2018 – 2023
Pittsburgh, PA
Carnegie Mellon University Ph.D. in Chemical Engineering

  • Developed optimization models for pressure swing adsorption processes in carbon capture systems.
  • Developed a machine learning pipeline for learning surrogate models of materials adsorption properties.
  • Proposed a mathematical-optimization-based crystalline nanomaterials design framework.

2014 – 2018
Tianjin, China
Tianjin University B.S. in Chemical Engineering

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