About — Design Informatics

WELCOME TO THE DILAB

Design Informatics Lab (DILab) is a research laboratory that aims to teach computers to assist designers in their creative process. Our research focuses on developing design exploration methods and tools that utilize the intersection of design, data science, and information technology. We are interested in three interdisciplinary areas:

Design Quantification & Automation,

Computer-Coordinated Design System,

Interaction Techniques & Devices.

We welcome collaboration with academic institutions, companies, and public organizations to advance the field of design and support designers' creativity. If you are interested in collaboration please contact us at: hoonhello@hanyang.ac.kr

디자인 인포매틱스 연구실 (Design Informatics Lab; 이하 DILab)은 디자이너의 창의성을 지원하기 위한 혁신적인 인간-컴퓨터 협업 방식에 대한 연구를 활발하게 수행하고 있습니다. DILab은 디자인 과정을 돕기 위한 디자인 자동화 방법 및 시스템을 개발하고 있으며, 디자인, 데이터 과학, 정보 기술 간 최첨단의 교차 지점을 포착하고 구현합니다. 이를 근간으로, 학술 기관, 기업, 그리고 공공기관과의 협업의 기회를 열어가고 있습니다. DILab은 세가지 분야의 학제 간 연구에 관심을 두고 있습니다:

디자인 정량화 및 자동화,

컴퓨터-협응형 디자인 시스템,

상호작용 기술 및 장치.

Research keywords:

Computational Design

Design Automation

Design Exploration

Human-AI Collaboration

Design Quantification & Automation

This research area focuses on the intersection of data analysis, genetic algorithms, and deep learning, and requires interdisciplinary knowledge. DILab promotes research that quantifies and automates design processes and outcomes based on engineering knowledge. Our research aims to develop algorithms and tools that can analyze and generate designs based on specified parameters. We welcome collaboration with researchers from diverse backgrounds to advance the field of design and engineering.

해당 연구 분야는 데이터 분석과 딥러닝·유전 알고리즘 등과 결합하여 폭넓은 학제 간 연구를 의미합니다. 디자인 인포매틱스 연구실은 공학적 지식을 기반으로 디자인 프로세스 와 디자인 결과물을 정량화하고, 이를 자동화하는 연구를 진행합니다.

Example Papers:

Analysis of Pairings of Colors and Materials of Furnishings in Interior Design with a Data-Driven Framework
Journal of Computational Design and Engineering (2022) 9.6: 2419-2438

SCIE
(Computer Science, Artificial Intelligence; Engineering, Multidisciplinary, IF=6.167)
Balancing Homogeneity and Heterogeneity in Design Exploration by Synthesizing Novel Design Alternatives based on Genetic Algorithm and Strategic Styling Decision
Advanced Engineering Informatics (2018) 38: 113-128.
SCIE
(Environmental Science; Green, Sustainable Science, Technology, IF=2.075)
The Gap between Design Intent and User Response: Identifying Typical and Novel Car Design Elements among Car Brands for Evaluating Visual Significance
Journal of Intelligent Manufacturing (2017) 28.7: 1729-1741
SCIE
(Computer Science, Artificial Intelligence; IF=3.667)
Style Synthesis and Analysis of Car Designs for Style Quantification based on Product Appearance Similarities
Advanced Engineering Informatics (2015) 29.3: 483-494
SCIE
(Computer Science, Artificial Intelligence; IF=2.000)

Computer-Coordinated Design System

The research area focuses on developing methods and systems that assist designers' creativity, aid design exploration, collaboration, and implementation. DILab aims to lead computational design research by developing algorithms for design exploration and generation, and by applying them to the design process. Our research is centered around designers and their needs, and we aim to develop support methods and systems that empower them in their work. We welcome collaboration with researchers, designers, and industry partners to advance the field of computational design.

해당 연구 분야는 디자인 탐색·협업·구현 과정을 지원하는 디자이너 중심 지원 방법 및 시스템을 개발하여 디자이너의 창의성을 확장하는 목적을 지니고 있습니다. 디자인 인포매틱스 연구실은 디자인 탐색 및 생성 알고리즘 등을 개발하고 이를 디자인 과정에 적용하는 컴퓨테이셔널 디자인 연구를 선도합니다.

Example Papers:

BIGaze: An eye-gaze action-guided Bayesian information gain framework for information exploration
Advanced Engineering Informatics (2023) 58: 102159

SCIE
(Computer Science, Artificial Intelligence; Multidisciplinary, IF=8.800)
CreativeSearch: Proactive design exploration system with Bayesian information gain and information entropy
Automation in Construction (2022) 142: 104502

SCIE
(Construction & Building Technology, IF=10.517)
BIGexplore: Bayesian Information Gain Framework for Information Exploration
ACM CHI 2022 Paper. New Orleans, USA

SCIE
(BKCSA003, h5-index=113)
Designer-Centric Spatial Design Support
Automation in Construction (2022) 137: 104195
SCIE
(Construction & Building Technology, IF=10.517)
3D Computational Sketch Synthesis Framework: Assisting Design Exploration Through Generating Variations of User Input Sketch and Interactive 3D Model Reconstruction
Computer-Aided Design (2020) 120: 102789
SCI
(Computer Science, Software Engineering, IF=2.947)

Interaction Techniques & Devices

This research area focuses on discovering novel interaction methods that improve the user experience. DILab is committed to continuously developing techniques and devices that create new visual, tactile, and immersive experiences. Our research explores the intersection of design and technology to develop innovative solutions that enhance user engagement, usability, and enjoyment. We welcome collaboration with researchers, designers, and industry partners to advance the field of interaction design and create impactful user experiences.

해당 연구 분야는 사용자 경험에 주목하여, 기존 경험을 개선하는 새로운 상호작용 방안을 발굴하는 것을 목표로 합니다. DILab은 새로운 시각적·촉각적·몰입적 경험을 생성하는 기술 및 장비를 꾸준히 연구하고 있으며, 나아가 도움이 필요한 사용자 경험을 고려한 사회적 기여 연구 또한 관심을 두고 있습니다.

Example Papers: