Namwoo Kang

Orcid: 0000-0003-3475-7477

According to our database1, Namwoo Kang authored at least 34 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2008
2010
2012
2014
2016
2018
2020
2022
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
BMO-GNN: Bayesian mesh optimization for graph neural networks to enhance engineering performance prediction.
J. Comput. Des. Eng., 2024

Deep generative model-based synthesis framework of four-bar linkage mechanisms with target conditions.
J. Comput. Des. Eng., 2024

Weighted unsupervised domain adaptation considering geometry features and engineering performance of 3D design data.
Expert Syst. Appl., 2024

Point-DeepONet: A Deep Operator Network Integrating PointNet for Nonlinear Analysis of Non-Parametric 3D Geometries and Load Conditions.
CoRR, 2024

Towards Robust Spatio-Temporal Auto-Regressive Prediction: Adams-Bashforth Time Integration with Adaptive Multi-Step Rollout.
CoRR, 2024

AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble.
CoRR, 2024

Vehicle Suspension Recommendation System: Multi-Fidelity Neural Network-based Mechanism Design Optimization.
CoRR, 2024

DeepJEB: 3D Deep Learning-based Synthetic Jet Engine Bracket Dataset.
CoRR, 2024

Enhancing Graph U-Nets for Mesh-Agnostic Spatio-Temporal Flow Prediction.
CoRR, 2024

Bayesian Mesh Optimization for Graph Neural Networks to Enhance Engineering Performance Prediction.
CoRR, 2024

Learning Design Preferences through Design Feature Extraction and Weighted Ensemble.
CoRR, 2024

Deep Generative Design for Mass Production.
CoRR, 2024

Deep Generative Model-based Synthesis of Four-bar Linkage Mechanisms with Target Conditions.
CoRR, 2024

Multi-objective Generative Design Framework and Realization for Quasi-serial Manipulator: Considering Kinematic and Dynamic Performance.
CoRR, 2024

Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective.
CoRR, 2024

2023
Topology optimization via machine learning and deep learning: a review.
J. Comput. Des. Eng., July, 2023

Adaptive neural network ensemble using prediction frequency.
J. Comput. Des. Eng., July, 2023

Performance Comparison of Design Optimization and Deep Learning-based Inverse Design.
CoRR, 2023

2022
Safety monitoring system of personal mobility driving using deep learning.
J. Comput. Des. Eng., 2022

Adaptive Neural Network Ensemble Using Frequency Distribution.
CoRR, 2022

Wheel Impact Test by Deep Learning: Prediction of Location and Magnitude of Maximum Stress.
CoRR, 2022

Deep Learning-Based Inverse Design for Engineering Systems: Multidisciplinary Design Optimization of Automotive Brakes.
CoRR, 2022

Generative Design by Reinforcement Learning: Enhancing the Diversity of Topology Optimization Designs.
Comput. Aided Des., 2022

2021
Explainable artificial intelligence for manufacturing cost estimation and machining feature visualization.
Expert Syst. Appl., 2021

2020
Autonomous Taxi Service Design and User Experience.
Int. J. Hum. Comput. Interact., 2020

Idle Vehicle Relocation Strategy through Deep Learning for Shared Autonomous Electric Vehicle System Optimization.
CoRR, 2020

Generative Design by Reinforcement Learning: Maximizing Diversity of Topology Optimized Designs.
CoRR, 2020

The Effect of Robo-taxi User Experience on User Acceptance: Field Test Data Analysis.
CoRR, 2020

Integrating Deep Learning into CAD/CAE System: Case Study on Road Wheel Design Automation.
CoRR, 2020

A Study on Anxiety about Using Robo-taxis: HMI Design for Anxiety Factor Analysis and Anxiety Relief Based on Field Tests.
CoRR, 2020

2019
Form + Function: Optimizing Aesthetic Product Design via Adaptive, Geometrized Preference Elicitation.
CoRR, 2019

Generative Design Exploration by Integrating Deep Generative Models and Topology Optimization.
CoRR, 2019

2014
Multidomain Demand Modeling in Design for Market Systems.
PhD thesis, 2014

2007
Integration of marketing domain and R&D domain in NPD design process.
Ind. Manag. Data Syst., 2007


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