7월 17일, 서울대학교 기계공학과 연사분들을 모시고 델프트공과대학교에서 반일 심포지엄을 개최합니다.
본 심포지엄은 재외과협 특별사업 “차세대 첨단산업 기술 국제협력 플랫폼 구축 사업” 과 델프트공대 기계공학부 High-Tech Theme의 지원을 받아 마련되었습니다.
이번 심포지엄에서는 기계공학을 중심으로 네덜란드와 한국 학계에서 수행되고 있는 다양한 스케일의 신기능 구조 설계, 제작 및 해석 기술을 소개하고,
Horizon Europe 공동과제 지원을 비롯한 다양한 공동연구 및 국제협력의 가능성을 함께 모색하고자 합니다.
심포지엄 참가는 무료이며, 관심 있는 분들의 많은 참여를 부탁드립니다.
참석 인원 파악을 위해 아래 행사 정보의 등록 링크를 통해 참석 의사를 알려주시면 감사하겠습니다.
또한, 13:00–14:00에 예정된 “Presentations by TU Delft Speakers” 세션에서 발표에 관심이 있으신 분은 별도로 연락 주시면 감사하겠습니다.
각 발표는 질의응답을 포함하여 약 10분간 진행될 예정이며, TU Delft 소속이 아니더라도 심포지엄의 주요 주제와 관련된 발표라면 참여하실 수 있습니다.
관련된 문의는 양지은 (jieun.yang@tudelf.nl)으로 편하게 연락해 주십시오.
감사합니다.
양지은 드림 (네덜란드과협 학술위원)
[ 행사 정보 ]
When: July 17, 2026, 13:00-18:00
Where: TU Delft Mechanical Engineering (Building 34) Lecture Hall A & Café Labs
Registration: https://forms.office.com/e/fcnxKcktg3
Program:
| 13:00-14:00 | ME Hall A | Presentations by TU Delft speakersWe’re currently confirming the list of speakers. If you’re interested in giving a presentation, please contact Jieun Yang (jieun.yang@tudelft.nl). |
| 14:00-14:15 | Coffee break | |
| 14:15-15:45 | Presentations by SNU speakersIntroduction Department of Mechanical Engineering, Seoul National University”AI-powered computational engineering: from bottom-up DNA self-assembly to top-down lithography” by Prof. Do-Nyun Kim”Recent advances in elastic metamaterials and reinforced learning based topology optimizations” by Prof. Joo Hwan Oh | |
| 15:45-16:00 | Coffee break | |
| 16:00-16:30 | Collaboration brainstorming session | |
| 16:30-18:00 | Café Labs | Borrel |
[ 서울대학교 연사 정보 및 초록 ]
AI-powered computational engineering: from bottom-up DNA self-assembly to top-down lithography
Do-Nyun Kim, AI-driven Simulation and Design Laboratory (http://aisdl.snu.ac.kr/)
Abstract: Recent advances in scientific and industrial AI have led to a paradigm shift in computational engineering. In this presentation, I will present our recent efforts to expedite the analysis-design validation process by using AI-powered computational methods. Two applications will be introduced: DNA origami design in structural DNA nanotechnology and lithography simulation in semiconductor manufacturing. First, I will present a multiscale modeling approach for DNA origami called SNUPI and how it is used to develop a generative design method powered by a graph neural network and a diffusion AI model. Then, I will present how we make lithography simulation fast and scalable by using neural operators.
Bio: Prof. Do-Nyun Kim has received his bachelor’s (2000) and master’s (2002) degrees from Seoul National University. He was a full-time instructor at the Korea Air Force Academy from 2002 to 2005. After receiving his Ph.D. (2009) in the Department of Mechanical Engineering at MIT, he worked as a postdoctoral associate in the Department of Biological Engineering at MIT. He joined as a faculty member in the Department of Mechanical Engineering at Seoul National University in 2013. He founded the NEXTMI Co., Ltd. in 2024 and has served as CEO since then. His research fields include industrial and scientific machine learning with a major focus on semiconductor manufacturing, structural DNA/RNA nanotechnology, and mechanical metamaterials.
Recent advances in elastic metamaterials and reinforced learning based topology optimizations
Joo Hwan Oh, Metastructure Lab. (https://metastruct.snu.ac.kr/)
Abstract: In this presentation, I will share recent advances in structural design to tailor structural performance. In particular, I will focus on two major research areas: metamaterials and topology optimization. The first part of the presentation is devoted to metamaterials, artificial materials composed of sub-wavelength unit-cell structures that enable unconventional wave manipulation. I will introduce a broad range of studies, from classical vibration isolation and wave attenuation to recent developments in multiphysics metamaterial systems. In the second part, I will present reinforcement learning-based topology optimization methods that integrate recent advances in artificial intelligence with topology optimization. These approaches demonstrate how AI can significantly improve the efficiency and capability of structural design.
Bio: Prof. Joo Hwan Oh received his B.S. in 2008 and Ph.D. in 2014 from Seoul National University. He began his academic career in 2016 at the Ulsan National Institute of Science and Technology (UNIST), where he served as an Assistant Professor and later as an Associate Professor until 2024. In 2024, he joined Seoul National University, where he is currently an Associate Professor in the Department of Mechanical Engineering. His research interests include elastic waves, elastic metamaterials, and topology optimization. Much of his work has focused on the development of novel elastic metamaterials and wave-based devices enabled by them. His current research focuses on emerging approaches to elastic metamaterials, including tunable and advanced elastic metamaterials, as well as their design methodologies based on reinforcement learning techniques.