publications

papers

2024

  1. deep-generative-design-for-mass-production.png
    Deep Generative Design for Mass Production
    Jihoon Kim*, Yongmin Kwon*, and Namwoo Kang
    2024
    arXiv PDF Blog

    AI-generated designs often can’t be mass-produced. This work converts 3D design problems into 2D depth images, embedding manufacturing constraints directly into the generative process—producing designs ready for die casting or injection molding.

  2. LinkGAN-framework.png
    Deep generative model-based synthesis framework of four-bar linkage mechanisms with target conditions
    Sumin Lee*, Jihoon Kim*, and Namwoo Kang
    Journal of Computational Design and Engineering, 2024
    HTML PDF Code

    Designing mechanical linkages that trace specific paths while handling forces is tedious. This conditional GAN generates multiple valid four-bar mechanisms instantly from motion/force requirements, replacing manual iteration with specification-driven synthesis.

2023

  1. perf-comp-framework.png
    Performance Comparison of Design Optimization and Deep Learning-based Inverse Design
    Minyoung Jwa*, Jihoon Kim*, Seungyeon Shin, and 3 more authors
    2023
    arXiv

    When should you use deep learning inverse design over traditional optimization? This benchmark systematically compares both approaches, identifying when each method excels—providing evidence-based guidance instead of hype.

conferences

2025

  1. KSME
    A Study on 3D Topology Optimization Shape Reconstruction with CSG-Based Deep Learning
    Jangseop Park, Jihoon Kim, Wonje Jang, and 3 more authors
    In KSME Annual Conference (Poster), 2025

2024

  1. ACSMO
    Deep Generative Design for Manufacturing: Meeting the Design Constraints of Casting and Injection Molding
    Jihoon Kim, Yongmin Kwon, and Namwoo Kang
    In Asian Congress of Structural and Multidisciplinary Optimization (ACSMO), 2024
  2. KSME
    2D Diffusion Model-based 3D Design Optimization for Mass Production
    Jihoon Kim, Yongmin Kwon, and Namwoo Kang
    In KSME Annual Conference, 2024
  3. KSME
    Deep Generative Design for Mass Production
    Jihoon Kim, Yongmin Kwon, and Namwoo Kang
    In KSME CAE Division Spring Conference, 2024

2023

  1. IDETC
    Deep Generative Model-based Synthesis of Four-bar Linkage Mechanisms Considering Both Kinematic and Dynamic Conditions
    Sumin Lee, Jihoon Kim, and Namwoo Kang
    In ASME International Design Engineering Technical Conferences (IDETC), 2023
  2. KSME
    Deep Learning-based Parametric Inverse Design Considering Engineering Performance and Additive Manufacturing
    Jihoon Kim, Sumin Lee, and Namwoo Kang
    In KSME Annual Conference, 2023
  3. KSME
    Deep Learning-based Four-bar Linkage Mechanism Design Considering Dynamic Conditions
    Jihoon Kim, Sumin Lee, and Namwoo Kang
    In KSME CAE Division Spring Conference, 2023