Kyung-Hoon Hyun
Hanyang University
About the Lab
Professor Kyung-Hoon Hyun's research lab focuses on advancing design intelligence through the integration of emerging technologies such as 3D generative AI, augmented reality (AR), and spatial data analytics. The lab explores how design processes—particularly in architecture and interior design—can be enhanced by optimizing user experience, spatial connectivity, and cognitive efficiency. Key research directions include the development of AI-driven CAD systems, AR-based e-commerce experiences, and data-driven floor plan analysis for residential design innovation.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
8Space designers use existing design references for creative inspiration. However, designers' creative processes can be influenced by the representation and the amount of information that the design references contain. In this respect, researchers on design creativity conducted studies to assist designers when utilizing design references. However, previous literature does not consider the connectivity of spaces, even though it is an essential architectural element that defines space circulation.
연구배경 고객이 직접 매장에 가지 않더라도 편리하게 상품을 구매할 수 있는 편리성 덕분에 온라인 커머스(E-commerce) 시장은 매년 꾸준히 성장해오고 있다. 그렇지만, 온라인 커머스에서 상품에 대한 정확한 정보가 제공되지 않을 경우, 여전히 고객들은 실제 제품의 크기, 형태, 디테일을 확인을 위해 오프라인 매장에 방문하고 있다. 이에 증강현실 기술을 활용한 AR 커머스는 온라인 커머스 및 오프라인 매장의 새로운 대안으로 떠오르고 있다. 여러 연구들을 통해, AR 커머스는 고객들의 구매 결정 과정에 긍정적인 영향을 주는 것으로 밝혀지고 있다. 그러나, 소비자가 아닌 사용자의 입장에서 AR 커머스 서비스의 사용 경험을 파악하기 위한 시도는 거의 이루어지고 있지 않다. 이에, 본 연구는 제품 정보의 명확한 전달 및 사용자의 범용적인 쇼핑 경험을 지원하기 위해 AR 커머스가 고려해야할 UX 요소를 찾고, 이를 개선하기 위한 방법을 제안한다. 연구방법 먼저, 사용자들이 AR 커머스에 대
Background Recent advancements in 3D generative artificial intelligence (AI) have streamlined design processes by enabling rapid model creation. However, these tools frequently lack the accuracy and comprehensive support needed for intricate real-world applications. Consequently, designers continue to depend on command-based computer-aided (CAD) tools such as Rhino, which provide the necessary accuracy but can impose high cognitive loads. To address these challenges, we introduce BIGcad:a workfl
Due to the continuous growth of the online store market, which has been futher accelerated by the Covid-19 pandemic, online stores have become an essential part of our daily lives. However, the limitation of online shopping is that customers cannot directly touch and feel the products. Product information plays a significant role in customers’ purchasing decisions, especially for expensive and low-frequency products such as furniture, where customers make an effort to obtain more accurate inform
Interior design is intricate, as the designer should consider numerous design elements such as circulation, spatial composition, and energy efficiency. The complex interior design process involves both divergent and convergent thinking. In divergent design thinking, designers use micro- and macrostrategies. If we can identify a designer’s strategies in the design process, we can support the designers in diversifying and embodying their design ideas. Therefore, we propose a novel method that auto
When dealing with Korean residential spaces, studying apartments is necessary for socio-cultural context. How did the apartments affect people's lifestyles? Researchers analyzed the spatial structure of the unit plan of the apartment to figure out the answer. This paper aims to inspire residential space designers to create novel and satisfying apartments and support the floor plan retrieval and generation system that considers residents' demand by analyzing Korean apartments' unit plans from var
Background Generative artificial intelligence (AI) is increasingly integrated into design practice, yet how these generative AI-driven design support system interface frameworks shape the designers’ workflow remains underexplored. To address this gap, we formalized and compared three generative AI-driven interfaces: Agentic Prompt-Based (AB), Programming Node-Based (PB), and Creative Node- Based (CB). Studying their influence requires methods that capture workflow dynamics beyond micro- level ac
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