Welcome to AiM⁴ Lab — Laboratory for AI-powered Modeling in Mechanics, Materials, and Manufacturing (지능형 설계 및 제조 연구실).
AiM⁴ Lab(지능형 설계 및 제조 연구실)은 AI를 모델링, 설계, 최적화의 강력한 도구로 활용하여 기계·재료·제조 공학의 지능화를 추구합니다. 다물리 모델링과 AI의 융합을 통해 데이터 효율적이고 직관적인 공학 시스템을 개발하며, 제조, 모빌리티, 전자, 에너지 분야의 문제 해결을 목표로 합니다. 연구 참여 및 연구실 입학, 공동 연구, 또는 기술 협력에 관심 있으신 분은 유승화 교수 이메일 ryush@kaist.ac.kr로 연락주시기 바랍니다. 현재, PRISM-AI 센터를 통해 Postdoc을 모집하고 있으니 많은 관심 부탁드립니다 [link].
At AiM⁴ Lab, we develop intelligent, physics-informed engineering systems by integrating artificial intelligence with solid mechanics, materials science, and multiphysics modeling. We aim to create data-efficient, adaptive, and human-centered methods for modeling, design, and optimization, pursuing a large-scale collaboration on manufacturing AI via PRISM-AI research center [link].
Our research tackles real-world challenges across manufacturing, mobility, electronics, and energy through:
Advanced modeling of solid mechanics and coupled physical phenomena
Integration of AI with simulation and experimental data for design and process optimization
Human-AI interfaces powered by large language models and multi-agent systems
We actively collaborate with partners in academia and industry who share our vision for intelligent, next-generation engineering. For inquiries about joining the lab, collaboration, or AI-based engineering solutions, please contact Prof. Seunghwa Ryu at ryush@kaist.ac.kr.
FYI, on strategic data-driven design—particularly our well-established AI surrogate-based inverse design strategies [link to the review paper],
Lecture in Korean: [AI기반 설계 및 제조업 적용 사례 Youtube강의][Slide_MerricVER] [Slide_SamsungVER]
Lecture in English: [AI Based Design and Homogenization, Youtube Lec (ENG)] [Slide_AnsysVER] [Slide_SJTU-UM_VER] [Slide_Stanford_VER] [Slide NCSU_VER]
A new perspective seminar materials, integrating physics-informed machine learning (PIML), large language models (LLMs), and digital twins, will be released soon. Stay tuned! As a preview, check out our perspective article [link].