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Sangjoon Bob Lee
411 posts
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Sangjoon Bob Lee
@bobleesj
Materials Science and Engineering PhD Student at Stanford University
New York
bobleesj.github.io
Joined September 2016
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  • Pinned
    user avatar
    Sangjoon Bob Lee
    @bobleesj
    Apr 19, 2025
    I'm excited to have contributed to a paper published in JACS! Here, I generated ~90 crystal physics-based features for ~2,000 .cif files using my cifkit Python package. Colleagues from CUNY and IIT then applied clustering models and experimentally validated the predictions.
    user avatar
    J. Am. Chem. Soc.
    @J_A_C_S
    Apr 19, 2025
    Unsupervised Machine Learning Prediction of a Novel 1:3 Intermetallic Phase with the Synthesis of TbIr3 (PuNi3-type) as Experimental Validation | Journal of the American Chemical Society @kgpians @Hunter_College pubs.acs.org/doi/10.1021/ja…
    445
  • user avatar
    Sangjoon Bob Lee
    @bobleesj
    Jan 29, 2025
    Herein Digital Discovery, I published 3 Python tools I built. From featurization to classification, if you ask me, it looks promising... doi.org/10.1039/D4DD00…
    237
  • user avatar
    Sangjoon Bob Lee
    @bobleesj
    Dec 17, 2024
    I am happy to contribute to the following paper. Our inorganic compositional descriptor dataset (OLED) has been used for training classical ML in predicting thermoelectric properties. It's performing pretty well.
    pubs.acs.org
    Thermoelectric Material Performance (zT) Predictions with Machine Learning
    Abstract. Research efforts using the tools in machine- and deep learning models have begun to show success in predicting target properties such as thermoel
    295
  • user avatar
    Sangjoon Bob Lee
    @bobleesj
    Dec 5, 2024
    Thanks for using the graphics (left) generated with my Python software, CIF Bond Analyzer (github.com/bobleesj/cif-b…). This looks like an incredible opportunity! ssmcci.chem.wisc.edu/about/
    182
  • user avatar
    Sangjoon Bob Lee
    @bobleesj
    Nov 15, 2024
    My Python package is now available on the Journal of Open Source Software (JOSS). The package extracts numerical descriptors from .cif files for (1) structural analysis and (2) generating features for ML models. joss.theoj.org/papers/10.2110…
    164

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