Taro Narahara
Associate Professor, NJ School of Architecture
- taro.narahara@njit.edu
- 677 Weston Hall (WEST)
About Me
Taro Narahara is an Associate Professor at the Hillier College of Architecture at NJIT. He has been recognized for his AI/ML-driven floor plan analysis, published in IEEE TMM and SIGGRAPH, and received the 2021 IDR Excellence Award (NII) and the 2020 Human Communication Award (IEICE). As a PI (2022), he led NSF-funded projects in computational design for multifamily residential architecture and collaborated as a co-PI with biomedical engineers on rehabilitation robotics and gaming (2016). As a licensed architect, he had been associated with prestigious firms such as SOM and Gluckman Mayner Architects, contributing to award-winning projects including the Mori Art Museum.
Education
Doctor of Design; Harvard University; Design; 2010
M.S.; Massachusetts Institute of Technology; Design and Computation in Architecture Studies; 2007
M.Arch.; Washington University in St Louis; Architecture; 1997
B.S.; Waseda University, School of Science and Engineering; Mathematics; 1994
Experience
The Institute of Science Tokyo (Tokyo Institute of Technology)
Overseas Adviser, October 2024 -
Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo
Visiting Scholar, September 2025 - August 2026
The Institute of Technology in Architecture (ITA), ETH
Visiting Scholar (Academic Guest), September 2018 - August 2019
Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo
Visiting Scholar, September 2018 - August 2019
Gluckman Tang Architects (formally Gluckman Mayner)
Architect, 2000 -
Skidmore, Owings & Merrill LLP (SOM)
Architect, 1997 -
Awards & Honors
Website
2026 Fall Courses
USYS 790A - DISSERTATION RESEARCH
ARCH 464 - OPTIONS STUDIO II
USYS 725 - INDEPENDENT STUDY I
USYS 726 - INDEPENDENT STUDY II
USYS 790D - DISSERTATION RESEARCH
USYS 790B - DISSERTATION RESEARCH
ARCH 463 - OPTIONS STUDIO I
USYS 792 - PRE-DOCTORAL RESEARCH
ARCH 689 - AI / VR IN ARCHITECTURE
Teaching Interests
I enjoy fostering creativity that is unbounded by current tools' capabilities or limitations. I embrace the challenge of inventing new methodologies alongside my graduate and undergraduate students at all levels.
Past Courses
Research Interests
My research integrates computational technology and AI with design, focusing on advanced machine learning, immersive virtual reality, and innovative interfaces to enhance the qualitative aspects of the design process. With a foundation in architecture and mathematics, I have developed predictive models for subjective dwelling comfort, user-friendly interfaces for sustainable building design, and game interactions across various fields. A significant part of my work involves understanding architects' decision-making processes to improve spatial design quality. Additionally, I am committed to fostering interdisciplinary collaborations and entrepreneurial initiatives, potentially establishing a platform to bring academic research to market.
In Progress
AI/ML Applications in Architecture
<b>Attractiveness Prediction for Real Estate Floor Plans:</b><br>Our pioneering work, detailed in <i>"Subjective Functionality and Comfort Prediction for Apartment Floor Plans and Its Application to Intuitive Online Property Search"</i> in IEEE Transactions on Multimedia (TMM) 2022, introduced a novel machine-learning model to accurately predict subjective apartment features. We developed a dataset assessing residential floor plans on comfort, openness, and privacy, designed an algorithm for score prediction, and integrated this into a user-centric apartment search tool. A comprehensive crowdsourced usability study confirmed the system's enhanced user experience. In collaboration with the University of Tokyo, this project yielded a predictive model for apartment functionality and comfort, resulting in notable awards, a leading journal publication, and a patent filing.<br><br><b>Generative Design for Sustainable Architecture:</b><br>This research, detailed in <i>"Sketch to Build: An Intuitive Design Platform for Sustainable Housing"</i> in the Annual Modeling and Simulation Conference (ANNSIM) 2022, funded by the NSF Innovation Corps (I-Corps™) program, facilitates an understanding of the relationship between design and performance, encouraging innovative, sustainable solutions that align with global standards like the UN's Sustainable Development Goals, and empowers architects to integrate creative and qualitative aspects into their design processes.<br><br><b>Speculative Visions for Transformative Architecture:</b><br>As technology evolves, hypothetical scenarios such as car-free cities, autonomous drones, rideshares, and AI-driven new services prompt a reassessment of design research values. These scenarios challenge us to broaden our understanding of cultural dynamics in public spaces. My recent publications, including SIGGRAPH 2018 and 2022, detail a series of research on speculative visions inspired by technological convergence.
<b>Attractiveness Prediction for Real Estate Floor Plans:</b><br>Our pioneering work, detailed in <i>"Subjective Functionality and Comfort Prediction for Apartment Floor Plans and Its Application to Intuitive Online Property Search"</i> in IEEE Transactions on Multimedia (TMM) 2022, introduced a novel machine-learning model to accurately predict subjective apartment features. We developed a dataset assessing residential floor plans on comfort, openness, and privacy, designed an algorithm for score prediction, and integrated this into a user-centric apartment search tool. A comprehensive crowdsourced usability study confirmed the system's enhanced user experience. In collaboration with the University of Tokyo, this project yielded a predictive model for apartment functionality and comfort, resulting in notable awards, a leading journal publication, and a patent filing.<br><br><b>Generative Design for Sustainable Architecture:</b><br>This research, detailed in <i>"Sketch to Build: An Intuitive Design Platform for Sustainable Housing"</i> in the Annual Modeling and Simulation Conference (ANNSIM) 2022, funded by the NSF Innovation Corps (I-Corps™) program, facilitates an understanding of the relationship between design and performance, encouraging innovative, sustainable solutions that align with global standards like the UN's Sustainable Development Goals, and empowers architects to integrate creative and qualitative aspects into their design processes.<br><br><b>Speculative Visions for Transformative Architecture:</b><br>As technology evolves, hypothetical scenarios such as car-free cities, autonomous drones, rideshares, and AI-driven new services prompt a reassessment of design research values. These scenarios challenge us to broaden our understanding of cultural dynamics in public spaces. My recent publications, including SIGGRAPH 2018 and 2022, detail a series of research on speculative visions inspired by technological convergence.
Other
Conference Paper
Conference Proceeding
Journal Article
Chapter
Translation or Transcription
Professional