BOgen: Generating Part-Level 3D Designs Based on User Intention Inference through Bayesian Optimization and Variational Autoencoder. - Seung Won Lee 004; Jiin Choi 001; Kyung Hoon Hyun (CoRR, 2023)

BIGaze: An eye-gaze action-guided Bayesian information gain framework for information exploration. - Seung Won Lee 004; Hwan Kim; Taeha Yi; Kyung Hoon Hyun (Adv. Eng. Informatics, 2023)

The Impact of Sketch-guided vs. Prompt-guided 3D Generative AIs on the Design Exploration Process. - Seung Won Lee 004; Tae Hee Jo; Semin Jin; Jiin Choi 001; Kyungwon Yun; Sergio Bromberg; Seonghoon Ban; Kyung Hoon Hyun (CHI, 2024)

GenPara: Enhancing the 3D Design Editing Process by Inferring Users' Regions of Interest with Text-Conditional Shape Parameters. - Jiin Choi 001; Seung Won Lee 004; Kyung Hoon Hyun (CHI, 2025)

Modeling Sequential Design Actions as Designer Externalization on an Infinite Canvas. - Yejin Yun; Seung Won Lee 004; Jiin Choi 001; Kyung Hoon Hyun (CHI Extended Abstracts, 2026)