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General Information

Full Name Kun-Lin Wu
Summary A research scientist with a passion in using data to solve real-world problems. 5+ years of research experience specializing in quantum simulation and machine learning for material developments, including catalysts for carbon capture and battery materials. Collaborated with scientists from universities, national labs and energy companies. Experienced in teaching, presentations and scientific publications. Strived to contribute cutting-edge discoveries through data-driven innovations.
Languages Chinese, English

Education

  • 2025
    PhD in Chemical Engineeering
    University of California, Davis, USA
    • Thesis title: The kinetics and dynamics of CO2 adsorption in zeolite material under humid environment
    • Advisor: Ambarish Kulkarni
  • 2020
    M.S. in Chemical Engineering
    University of Washington, Seattle, USA
    • Thesis title: Pharmacological Regulation of Protein-Polymer Hydrogel Stiffness
    • Advisor: Cole DeForest
  • 2017
    B.S. in Chemical Engineering
    National Taiwan University, Taipei, Taiwan

Experience

  • 2020 - 2025
    Graduate Student Researcher
    University of California, Davis
    • Developed a theory and numerical implementation for modeling CO2 adsorption in catalyst under humid condition.
    • Advisor: Ambarish Kulkarni
  • 2024
    Research Assistant
    Quantum Simulations Group, Lawrence Livermore National Lab
    • Developed models for electrode material to study lithium de-solvation process at the electrolyte-electrode interface.
    • Advisor: Sabrina Wan
  • 2018-2020
    Graduate Student Researcher
    University of Washington, Seattle
    • Employed protein engineering and molecular biology to design and synthesize biomaterials for drug delivery.
    • Advisor: Cole DeForest
  • 2017-2018
    Military Service
    National Taiwan Science Education Center, Taipei
    • Mandatory military service
  • 2015 - 2016
    Student Ambassador
    National Taiwan University, Taipei

Workshops

  • 2024
    NERSC GPU Hackathon
  • 2022
    Deep Modeling for Molecular Simulation Workshop

Honors and Awards

  • 2023
    • RSC Advances Outstanding Student Paper Awards

Technical Skills

  • Programming and Software
    • Python, Git/GitHub, Jupyter Notebook
  • High Performance Computing (HPC)
    • Shell script, parallel programming (MPI libraries)
  • Machine learning
    • Scikit-learn, TensorFlow, PyTorch, MACE
  • Scientific Computing
    • Density Functional Theory (DFT) Calculations (VASP, Quantum ESPRESSO)

Other Interests

  • I enjoy music, traveling, and cooking.