RESEARCH

Center for Data-driven Research for Materials and Universe

The Center for Data-driven Research for Materials and Universe, led by Prof. Jihoon Kim, sits within IDIS and manages the project “Material and Universe Data Measurement, Collection, and Modeling” which aims to revolutionize research methodologies by leveraging observation data from both microscopic and macroscopic scales. This initiative focuses on the following key areas:

Key Objectives and Activities:

1. Innovation in Research Methodologies:

  • Transition to “data-driven discovery research” methodologies using observation data that spans from the micro to the macro scale.
  • Integrate measurement data with theoretical numerical experiments based on quantum theory and cosmology.
2. Establishment of Data-Driven Research Infrastructure:
  • Develop a research foundation that combines measurement data with theoretical numerical experiments for comprehensive studies.
  • Facilitate interdisciplinary research by integrating data from various fields and developing common research methodologies such as data mining and machine learning.

Research Goals:

  • Transition and innovate research methodologies to data-driven discovery research based on observation data from the micro to the macro scale.
  • Establish a foundation for conducting research that integrates measurement data with theoretical numerical experiments based on quantum theory and cosmology.
  • Promote interdisciplinary research to derive new discoveries by integrating data accumulated across various fields and developing/sharing common research methodologies.

Research Groups and Sub-Projects:

1. Machine Learning-Based Physical Science Methodology Development Team (Ji-hoon Kim)

C-1-1:

Particle/Field Physics/Astrophysics (Dark Matter/Dark Energy): Parameter estimation for cosmic models using machine learning. (Ji-hoon Kim, LAMP faculty)

C-1-2:

Astronomy/Astrophysics (Extragalactic/Observational Cosmology): Comparative study of large-scale spectroscopic surveys and numerical simulations using machine learning. (Jubee Sohn, LAMP faculty)

C-1-3:

Electrochemistry/Photochemistry/Convergence Chemistry (Material Electrochemistry): Development of data-driven electrocatalyst materials for carbon neutrality. (Yun Jeong Hwang, LAMP faculty)
2. Data-Driven Earth and Planetary Exploration Team (Sang-Moo Lee)

C-2-1:

Atmospheric Science (Observation/Remote Sensing): Earth environment remote sensing using microwaves based on big data and AI learning methods. (Sang-Moo Lee, LAMP faculty)

C-2-2:

Earth/Geological Sciences (Economic/Resource Geology): Data-driven exploration of energy and mineral resources in the Earth’s crust, oceans, and planets. (Jung Hun Seo, LAMP faculty)

C-2-3:

Earth/Geological Sciences (Stratigraphy/Sedimentology): Establishment of planetary geology research using 3D terrain modeling. (Jusun Woo, LAMP faculty)

This project is supported by the SNU Center for LAMP project and aims to create a robust framework for integrating measurement data with advanced theoretical models, driving new discoveries in material and universe sciences through data-driven methodologies and interdisciplinary collaboration.