[20210205 : Colloquium]
Data-Driven Methods for Artist-Directed Fluid Simulations
1. 일시 : 2021년 2월 5일 (금) 13:00-14:30
2. 장소 : 아산이학관 525호 및 Zoom을 이용한 실시간 온라인 강연 동시 진행
- Zoom링크 :
https://korea-ac-kr.zoom.us/j/
3. 연사 : 김병수 박사 (스위스취리히연방공과대학(ETH Zuric))
4. 제목 : Data-Driven Methods for Artist-Directed Fluid Simulations
5. 초록 : Fluid phenomena are ubiquitous to our world experience: winds swooshing through trembling leaves, turbulent water streams running down a river, and cellular patterns generated from wrinkled flames are some few examples. These complex phenomena capture our attention and awe due to the beautifully materialized complex patterns and become crucial elements to artistically support storytelling. In virtual environments, however, sophisticated manipulation of animated flow structures is still a burdensome task. Given the amount of available fluid simulation data, data-driven approaches have emerged as attractive solutions. In this talk, I will present our recent works on data-driven methods for art-directable fluid simulations.
6. 연사소개 : Byungsoo Kim recently completed his joint PhD at Computer Graphics Lab at ETH Zurich and Disney Research Studios, where Prof. Markus Gross has advised him. His research mainly focuses on deep learning methods for art-directable fluid simulations. Prior to that, he received a BSc in Computer Science from KAIST in 2009 and an MSc in Computer Science from ETH Zurich in 2016 after 4 years of working as a research engineer in Graphics industry. (Website: www.byungsoo.me)