🌟 Research Interests

Design for Additive Manufacturing

• Topology Optimization

• Decomposition Optimization

• Multi-material and Cost-effective Structures

Representative Papers

• Kim H, Kim IY* (2024) 3D decomposition optimization of topology-optimized structures considering a build volume constraint for additive manufacturing. Computer Methods in Applied Mechanics and Engineering 432:117357.
• Kim H, Crispo L, Patel A, Galley N, Yeon SM, Son Y, Kim IY* (2024) Design of a metal additive manufactured aircraft seat leg using topology optimization and part decomposition. Rapid Prototyping Journal 30(5):947–969.

Data-driven Design

• Reliable Decision-making

• Global Predictive Model

• Physics-informed Machine Learning

Representative Papers

• Kim H, Lee TH* (2022) Design-target-based optimization using input variable selection and penalty-Lagrange multiplier for high-dimensional design problems. Structural and Multidisciplinary Optimization 65:258.
• Kim H, Lee TH* (2021) A robust elastic net via bootstrap method under sampling uncertainty for significance analysis of high-dimensional design problems. Knowledge-Based Systems 225:107117.
• Kim H, Lee TH,* Kwon T (2021) Normalized neighborhood component feature selection and feasible-improved weight allocation for input variable selection. Knowledge-Based Systems 218:106855.

Design for Mobility Components

• Lightweight Structures

• Crashworthiness Certification

• Accelerated Life Testing

Representative Papers

• Kim H, Crispo L, Patel A, Galley N, Yeon SM, Son Y, Kim IY* (2024) Design of a metal additive manufactured aircraft seat leg using topology optimization and part decomposition. Rapid Prototyping Journal 30(5):947–969.
• Ha DH, Kim H,* Lee TH* (2022) Scenario-based multidisciplinary optimization for a new accelerated life testing of electric traction motor and inverter system. Structural and Multidisciplinary Optimization 65:353.

Optimization Algorithms for ANNs

• Conjugate Gradient Methods

• Intelligent Robotic Grasping

• Digital Twin Systems

Representative Papers

• Kim S, Kim H,* Kang N, Lee TH* (2025) Projected variable three-term conjugate gradient algorithm for enhancing generalization performance in deep neural network training. Neurocomputing 657:131568.
• Kim H, Wang C, Byun H, Hu W,* Kim S, Jiao Q, Lee TH* (2023) Variable three-term conjugate gradient method for training artificial neural networks. Neural Networks 159:125–136.