Selected Recent Research Publications by Nagakura's ARC Group and Advisees at MIT Architecture Department
| [ML] | (architecture) | W. Peng, F. Zhang, T. Nagakura |
2017 conference |
2018 Smarchs Thesis |
| Machines’ Perception of Space: Employing 3D Isovist Methods and a Convolutional Neural Network in Architectural Space Classification |
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| [ML] | (architecture) | W. Peng |
2023 PhD Thesis |
demo video |
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Visual Experience in Temporal Situational Context: Method of Matching and Modeling in Design
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| [ML] | (architecture) | C. Cheng, T. Nagakura, D. Tsai |
2023 conference |
2024 Smarchs Thesis |
| A Synergy of AI Observation and Design Tool: Leveraging Multifaceted AI Techniques for Encoding Human Behaviors and Stories in Space
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| [ML] | (architecture) | S. Miao, T. Nagakura, D. Tsai |
2024 conference |
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Deep Spatial Memory: Quantifying Architectural Spatial Experiences through Agent-driven Simulations and Deep Learning
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| [ML] | (architecture) | C. Wu |
2020 MArch thesis |
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Machine learning in housing design : exploration of generative adversarial network in site plan / floorplan generation |
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| [ML] |
(architecture) |
H. Tu, G. Varinlioglu, L. Gao, B. Chen, T. Nagakura |
2023 conference |
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Feeling Like Humans: Low-cost wearable sensors for design research in the age of AI
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| [ML] |
(urbanism) |
R. Sanatani, T. Nagakura |
2023 conference |
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The Many Faces of the Metropolis: Unsupervised Clustering of Urban Environments in Mumbai Based on Visual Features As Captured in City-Wide Street-View Imagery
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| [ML] | (urbanism) | R. Sanatani, T. Nagakura, D. Tsai |
2022 conference
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Presentation Video (SIGraDi) |
| The Tourist's Image of the City: A comparative analysis of the visual features and textual themes of interest across three global metropolises
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| [ML] | (urbanism) | N. H. (Charles) Wu |
2022 Smarchs Thesis |
| Reasoning about Space Video via Pattern Language of Human Behavior by Extracting MultiAction Activities via Machine Learning Video |
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| [ML] | (heritage) | P. Gonzalez, T. Nagakura |
2020 conference |
2021 PhD thesis |
demo video |
| AI Visitor: Tracking and simulating pedestrian trajectories in Machu Picchu |
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| [ML] | (architecture) | R. Villalon |
2017 PhD Thesis |
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| Data mining, inference, and predictive analytics for the built environment with images, text, and WiFi data |
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| [ML] | (architecture) | X. Zhang |
2021 Smarchs Thesis |
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| Envisage: Investigating Design Intentions, Visual Perception through Eye Tracking of Architectural Sketches |
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| [ML] | (architecture) | J. Park |
2015 PhD Thesis |
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| Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education |
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| [ML] | (urbanism) | Q. Liang, M. Wang, T. Nagakura |
2020 conference |
2020 Smarchs Thesis |
Video |
| Urban Immersion: A Web-based Crowdsourcing Platform for Collecting Urban Space Perception Data. |
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| [ML] | (architecture) | J. Peraino |
2020 MArch thesis |
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| Architectural epidemiology : a computational framework |
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| [ML] | (architecture) | Y. Liu |
2020 Smarchs Thesis |
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| Measuring the immeasurable : an experiment for a machine to map low-level features to high-level semantic representation of architectural space using a single view photo |
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| [ML] | (urbanism) | T. Sun |
2020 Smarchs Thesis |
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| Synthesizing 3D morphology from a collection of urban design concepts |
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| [expert system] | (architecture) | W. Yi |
2024 Smarchs Thesis |
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| Data-driven Home Workspace Design: Interactive DIY Platform Mediating the User and Expert Literature |
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| [crowdsourcing] | (architecture) | J. Zhang |
2023 UG Thesis |
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| Crowdsourcing Feedback and Augmenting 3D Visualizations: Online Collaboration Tools for Gamified Participatory Design Workshops |
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| [affective comp.] |
(architecture) |
H. Tu |
2023 Smarchs Thesis |
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Analyzing Affective Responses to Virtual Spaces Using Physiological Sensors and Verbal Descriptions
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| [affective comp.] |
(urban design) |
G. Varinlioglu, H. Tu, T. Nagakura |
2023 conference |
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Affective Computing for Game User Research
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| [data mining] | (architecture) | T. Nagakura, W. Peng, Y. Lei |
2021 conference |
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| Representing Cultural Heritage Places through AR in Museums: Learning from the usage data sampled at the exhibition of Alva Aalto's Baker House |
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| [crowdsourcing] | (architecture) | I. As, T. Nagakura |
2016 Journal |
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ARCHITECTURE FOR THE CROWD BY THE CROWD: A NEW MODEL FOR DESIGN ACQUISITION
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| [crowdsourcing] | (architecture) | I. As, T. Nagakura |
2017 conference |
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Crowdsourcing the Obama Presidential Center: An Alternative Design Delivery Model: Democratizing Architectural Design
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| [crowdsourcing] | (urbanism) | Y. Yoshimura, S. He, G Hack, T Nagakura, C Ratti |
2020 conference |
2014 Smarchs Thesis |
| Quantifying Memories: Mapping Urban Perception |
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| [data mining] | (urbanism) | X. Chen |
2011 Smarchs Thesis |
demo video (Singapore) |
demo video (Paris) |
| Seeing differently : cartography for subjective maps based on dynamic urban data |
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| [data mining] | (urbanism) | N. Chen |
2016 Smarchs Thesis |
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| Urban data mining : social media data analysis as a complementary tool for urban design |
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| [data mining] | (architecture) | S. Zhang |
2020 MArch thesis |
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| Value in design? Features, pricing, and design strategies |
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