Rudi Stouffs

Associate Professor

National University of Singapore (NUS)

Singapore

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About

Rudi Stouffs is an Associate Professor at the National University of Singapore. His research focuses on urban form understanding, climate zone classification, and machine learning applications in architecture and urban planning. Recent publications include work on graph neural networks, unsupervised representation learning for architectural design, and modeling the impacts of land use on surface temperatures. His contributions aim to integrate advanced computational methods with practical insights for sustainable urban development.

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2025

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2022

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2021

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2021

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2020

Collaborators (5)

Clayton Miller

Assistant Professor

National University of Singapore (NUS)

SINGAPORE

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Helga Tauscher

Professor

HTW Berlin - University of Applied Sciences

GERMANY

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Mojgan Jadidi

Associate Professor

York University

CANADA

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Pengyuan Liu

University of Glasgow

UNITED KINGDOM

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Fernanda Leite

Professor

University of Texas at Austin

UNITED STATES

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Rudi Stouffs

Research Interests

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About

Articles (23)

SE-VGAE: Unsupervised disentangled representation learning for interpretable architectural layout design graph generation

Living upon networks: A heterogeneous graph neural embedding integrating waterway and street systems for urban form understanding

Assessing and optimizing cooling intensity of UGS via improved metrics: A study based on machine learning simulation model

Fine-grained local climate zone classification using graph networks: A building-centric approach

A dual-aspect evaluation framework for architectural-like plan generation via pix2pix series algorithms

Parametric archetype: An incremental learning model based on a similarity measure for building material stock aggregation

Simulating land surface temperature impacts of proposed land use and land cover plans using an integrated deep neural network approach

Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models

Sensing climate justice: A multi-hyper graph approach for classifying urban heat and flood vulnerability through street view imagery

Augmenting materials passports to support disassembly planning based on building information modelling standards

Mitigating operational greenhouse gas emissions in ageing residential buildings using an Urban Digital Twin dashboard

An integrated framework for jointly assessing spatiotemporal dynamics of surface urban heat island intensity and footprint: China, 2003–2020

Integrating SSPs and multi-model ensembles in exploring parameter relationships for vertical urban development using a 3D-UGM: A case study of Wuhan, China

Techniques and tools for integrating building material stock analysis and life cycle assessment at the urban scale: A systematic literature review

A data-driven agent-based model of occupants’ thermal comfort behaviors for the planning of district-scale flexible work arrangements

A predictive model for daylight performance based on multimodal generative adversarial networks at the early design stage

Simulation and prediction of daytime surface urban heat island intensity under multiple scenarios via fully connected neural network

Urbanity: automated modelling and analysis of multidimensional networks in cities

Assessing and benchmarking 3D city models

Virtual 3D City Models

A modular graph transformation rule set for IFC‐to‐CityGML conversion

Emerging topics in 3D GIS

Tools for BIM-GIS Integration (IFC Georeferencing and Conversions): Results from the GeoBIM Benchmark 2019

Collaborators (5)

Clayton Miller

Helga Tauscher

Mojgan Jadidi

Pengyuan Liu

Fernanda Leite

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