At the interface of

Mathematical Physics, Quantum Fields and Machine Learning

Our research group aims to unravel the physical phenomena and mathematical structures that underpin the source code of our universe.

Research Publications Team
Brane tiling and tropical coamoeba diagram

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    Selected work

    Research Highlights

    All research

    Unsupervised Machine Learning Techniques for Exploring Tropical Coamoeba, Brane Tilings and Seiberg Duality

    Rak-Kyeong Seong
    Phys. Rev. D 108, 106009 (2023)

    arXiv:2309.05702 DOI

    Machine Learning Regularization for the Minimum Volume Formula of Toric Calabi-Yau 3-folds

    Eugene Choi, Rak-Kyeong Seong
    Phys. Rev. D 109, 046015 (2024)

    arXiv:2310.19276 DOI

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    Student Recruitment

    If you are interested in joining our group as a graduate student or an undergraduate internship student, please contact Professor Rak-Kyeong Seong at seong@unist.ac.kr.

    Internship and graduate positions currently available
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    Support

    Our Funders

    The research group is supported by research grants from:

    National Research Foundation of Korea
    BK21 UNIST College of Natural Sciences

    Elsewhere

    Profiles and Repositories

    arXiv Pre-prints by Rak-Kyeong Seong Google Scholar Citations and h-index iNSPIRE-HEP High-energy physics literature AMS MathSciNet Mathematical reviews LinkedIn rak-kyeong-seong Twitter / X @rak_seong YouTube @rakkyeongseong Personal site www.rakkyeongseong.com