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 University)
Prof. Taegeun Song (Kongju National Universit)
Prof. Joo-Hyoung Lee (GIST)
There will be 7 talks. Tentative time table is as follows;
14:00 to 14:30 - Registration and greetings
14:30 to 16:00 - Session 1 (2 talks, Chair: In-ho Lee)
(1) [14:30-15:10] Seungwu Han: Machine learning potentials: paradigm shift in material simulation
(2) [15:10-16:00] Kang Joongoo: Theoretical study of nonfermionic thermoelectricity using machine-learned force fields
16:20 to 17:40 - Session 2 (2 talks on quantum machine learning for physical systems, Chair: Hunpyo Lee)
(1) [16:20-17:00] Daniel Kyungdeock Park: T.B.A
(2) [17:00-17:40] Dong-Hee Kim: Neural-network ansatz for variational many-body calculations
09:00 to 09:40 - Registration
09:40 to 10:20 - Session 3 (3 talks on machine learning for computational material and biological science, Chair: Heung-Sik Kim)
(1) [09:40-10:20] Juyong Lee: T.B.A
(2) [10:20-11:00] Taegeun Song: Machine learning approches in biological matter
(3) [11:00-11:40] Joo-Hyoung Lee: T.B.A
11:40 to 11:50 - Concluding remarks