Activities

  • Activities
  • Scientific Programs
  • Activities

    Scientific Programs

    Title Machine Learning on Condensed Matter Physics and Material Science
    Place Kangwon National University at Samcheok (Green Energy Building)
    Date 2022-08-29~2022-08-30 (Registerable Date : ~ 2022-08-27)
    Program Category 3
    Organizer Heungsik Kim (Kangwon National University )
    Hunpyo Lee (Kangwon National University at Samcheok)
    In-Ho Lee (KRISS)
    Poster Image
    Program SCOPE OF PROGRAM
    Machine learning and data-driven sciences and their applications to various fields of science and engineering, including condensed matter and materials physics, has been intensively studied recently. This TRP program aims to organize an informal-style gathering of condensed matter, materials physics and (quantum) machine learning researchers who independently have studied this emerging field of science, and to activate communication and collaboration between domestic and international researchers. Tentative subjects to be addressed are as follows;

    - Data driven discovery and inverse materials design.
    - Deep learning applications in physics and materials science.
    - Machine learning-accelerated numerical algorithms.
    - Quantum machine learning.

    LIST OF SPEAKERS
    Prof. Dong-Hee Kim (GIST)
    Prof. Seungwu Han (SNU)
    Prof. Joongoo Kang (DGIST)
    Prof. Juyong Lee (Kangwon National University)
    Prof. Daniel Kyungdeock Park (Yonsei University)
    Prof. Taegeun Song (Kongju National Universit)
    Prof. Joo-Hyoung Lee (GIST)

    PROGRAM SCHEDULE
    There will be 7 talks. Tentative time table is as follows;

    8/29 (Monday)
    14:00 to 14:30 - Registration and greetings
    14:30 to 15:50 - Session 1 (2 talks on machine learning for computational material science, Chair: In-Ho Lee)
    (1) [14:30-15:10] Seungwu Han: Machine learning potentials: paradigm shift in material simulation
    (2) [15:10-15:50] Joongoo Kang: Theoretical study of nonfermionic thermoelectricity using machine-learned force fields

    16:30 to 17:50 - Session 2 (2 talks on quantum machine learning for physical systems, Chair: Hunpyo Lee)
    (1) [16:30-17:10] Daniel Kyungdeock Park: Machine Learning in the Noisy Intermediate-Scale Quantum Computing Era
    (2) [17:10-17:50] Dong-Hee Kim: Neural-network ansatz for variational many-body calculations

    8/30 (Tuesday.)
    09:00 to 09:40 - Registration
    09:40 to 11:40 - Session 3 (3 talks on machine learning for computational material and biological science, Chair: Heungsik Kim)
    (1) [09:40-10:20] Juyong Lee: Retrosynthetic reaction pathway prediction through neural machine translation of atomic environments
    (2) [10:20-11:00] Taegeun Song: Machine learning approches in biological matter
    (3) [11:00-11:40] Joo-Hyoung Lee: Deep-learning-guided accelerated screening over materials space
    11:40 to 11:50 - Concluding remarks

    KTX 시간
    KTX 서울-동해: 11:01(서울역)-11:21(청량리역)--11:28(상봉역)-13:38(동해역)
    KTX 동해-서울: 14:00(동해역)-16:17(청량리역)-16:37(서울역)