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Steven Jige Quan

Seoul National University · 環境科学

研究室紹介

Professor Steven Jige Quan's research lab specializes in urban design computation, focusing on integrating artificial intelligence, urban form, and energy performance to address complex urban challenges. The lab explores smart design frameworks that leverage AI-aided design and generative models to empower both professionals and the public in urban design processes. Key research directions include 3D urban climate zone (LCZ) mapping, solar energy potential modeling, and the simulation of energy performance in relation to urban density, morphology, and context. The lab emphasizes data-driven, simulation-based approaches to support sustainable and equitable urban development.

urban design computationAI-aided designenergy performance modeling3D LCZ mappingsolar energy modeling

Research Overview

Papers
64
Total Citations
1,409
Papers (5y)
32
Primary Field
環境科学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
32total
2022
2023
2024
2025
2026
Citations per year (5y)
426total
20222023202420252026

Selected Papers

15
1
Review|127 citations·2021
Urban form and building energy use: A systematic review of measures, mechanisms, and methodologies
Steven Jige Quan, Chaosu Li
SJR Q1Renewable and Sustainable Energy Reviews
Building and ConstructionEngineering
2
Review|118 citations·2021
A systematic review of GIS-based local climate zone mapping studies
Steven Jige Quan, Parth Bansal
SJR Q1Building and Environment
Environmental EngineeringEnvironmental Science
3
Article|102 citations·2023
Examining temporally varying nonlinear effects of urban form on urban heat island using explainable machine learning: A case of Seoul
Parth Bansal, Steven Jige Quan
SJR Q1Building and Environment
Environmental EngineeringEnvironmental Science
4
Article|90 citations·2019
Artificial intelligence-aided design: Smart Design for sustainable city development
Steven Jige Quan, James Park, Athanassios Economou, Sugie Lee
SJR Q1Environment and Planning B Urban Analytics and City Science

Current planning and design decision support systems show limitations in the integration of design, science, and computation. Planning support systems with manual design and post-design evaluations impose major challenges in exploring huge design spaces. Generative design systems largely neglect the wicked nature of design problems and lack appropriate representation methods and simulation tools at the urban scale. To tackle those challenges, this research developed a Smart Design framework feat

Media TechnologyEngineering
5
Book Chapter|70 citations·2015
Urban Data and Building Energy Modeling: A GIS-Based Urban Building Energy Modeling System Using the Urban-EPC Engine
Steven Jige Quan, Qi Li, Godfried Augenbroe, Jason Brown, Perry Pei‐Ju Yang
SJR Q4Lecture notes in geoinformation and cartography
Building and ConstructionEngineering
6
Article|66 citations·2022
Urban-GAN: An artificial intelligence-aided computation system for plural urban design
Steven Jige Quan
SJR Q1Environment and Planning B Urban Analytics and City Science

The current urban design computation is mostly centered on the professional designer while ignoring the plural dimension of urban design. In addition, available public participation computational tools focus mainly on information and idea sharing, leaving the public excluded in design generation because of their lack of design expertise. To address such an issue, this study develops Urban-GAN, a plural urban design computation system, to provide new technical support for design empowerment, allo

Building and ConstructionEngineering
7
Article|60 citations·2016
Urban Form and Building Energy Performance in Shanghai Neighborhoods
Steven Jige Quan, Jiang Wu, Yi Wang, Zhongming Shi, Tianren Yang, Perry Pei‐Ju Yang
Energy ProcediaOA

Urban form is considered as two different concepts here: one as geometry and the other as a complex system. This paper uses simulation experiments to test the density and energy performance relationship in nine Shanghai neighborhoods, with the urban form defined as a complex system. The results show a complex pattern. When density is only related to geometry, the density seems to negatively impact building energy use intensity, following the widely perceived conclusion from previously studies. B

Environmental EngineeringEnvironmental Science
8
Article|57 citations·2022
Relationships between building characteristics, urban form and building energy use in different local climate zone contexts: An empirical study in Seoul
Parth Bansal, Steven Jige Quan
SJR Q1Energy and Buildings
Environmental EngineeringEnvironmental Science
9
Article|49 citations·2017
Local Climate Zone Mapping for Energy Resilience: A Fine-grained and 3D Approach
Steven Jige Quan, Florina Dutt, Erik Woodworth, Yoshiki Yamagata, Perry Pei‐Ju Yang
Energy ProcediaOA

The LCZs (Local Climate Zones) system and its mapping have been emerging in recent years as an important approach to study the variations of local climates in cities, which are closely linked to human comfort issues and building energy demand. However, most of the current practices of LCZs mapping are based on 2D satellite images that can only provide rough estimations. This study tries to improve the current LCZs mapping methods by proposing a bottom-up method that adopts high-resolution 3D bui

Environmental EngineeringEnvironmental Science
10
Article|48 citations·2015
A GIS-based Energy Balance Modeling System for Urban Solar Buildings
Steven Jige Quan, Qi Li, Godfried Augenbroe, Jason Brown, Perry Pei‐Ju Yang
Energy ProcediaOA

Solar buildings as one type of decentralized renewable energy systems have been widely adopted to reduce carbon emissions. Related policy making faces two questions: how much total solar energy can be produced in a city and what proportion of building energy use can be supplied by the solar power? These questions remain hard to answer because of the lack of appropriate modeling systems, due to the data inconsistency and the limitation of current building energy and solar potential modeling metho

Building and ConstructionEngineering
11
Article|46 citations·2014
Computing Energy Performance of Building Density, Shape and Typology in Urban Context
Steven Jige Quan, Athanassions Economou, Thomas Grasl, Perry Pei‐Ju Yang
Energy ProcediaOA

This paper aims to better understand the impact of urban context on building energy consumption. The factors of external shading, shapes generated from zoning ordinances, and local climate are examined concerning three main questions: (1) how density influences building energy consumption generally, (2) how a given density generates alternative building shapes that have different impacts on energy performance, and (3) how different typologies affect the energy-density relationship. To answer the

Environmental EngineeringEnvironmental Science
12
Article|32 citations·2024
Comparing hyperparameter tuning methods in machine learning based urban building energy modeling: A study in Chicago
Steven Jige Quan
SJR Q1Energy and Buildings
Building and ConstructionEngineering
13
Article|32 citations·2020
An exploration of the relationship between density and building energy performance
Steven Jige Quan, Athanassios Economou, Thomas Grasl, Perry Pei‐Ju Yang
SJR Q1URBAN DESIGN International
Building and ConstructionEngineering
14
Review|28 citations·2024
A review of surrogate-assisted design optimization for improving urban wind environment
Yihan Wu, Steven Jige Quan
SJR Q1Building and Environment
Environmental EngineeringEnvironmental Science
15
Article|17 citations·2025
Urban cooling and energy-saving effects of nature-based solutions across types and scales
Hailu Wei, Xiaohang Bai, Q. Lu, Jiyuan Wu, Fengmin Su, Tianzhen Hong, Qinran Hu, Wei Wang, Steven Jige Quan, Zhixing Luo, Yilong Han
Nature Cities
Environmental EngineeringEnvironmental Science

Research Areas

Building and ConstructionEnvironmental EngineeringGlobal and Planetary ChangeRenewable Energy, Sustainability and the EnvironmentMedia TechnologyTransportation

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