About
Jonathan Dortheimer is an architect, educator, researcher, and founder of the Architectural Artificial Intelligence Research Lab at Ariel University. His work examines how artificial intelligence, computational methods, and participatory technologies can support architectural design, urban planning, and more transparent decision-making.
Jonathan is a senior lecturer at the Ariel University School of Architecture and a guest scholar at the Chair of Architectural Informatics, Technical University of Munich in Germany.
He completed his doctoral studies in 2021 at Tel Aviv University under the supervision of Prof. Eran Neuman and Prof. Tova Milo. He later worked as a postdoctoral researcher at the Material Topology Research Lab at the Technion, in collaboration with the Future Automation Lab at Cornell Tech, under the supervision of Prof. Aaron Sprecher and Prof. Wendy Ju.
Jonathan’s research develops and evaluates computational tools for participatory design, urban AI, and urban digital twins. Across these areas, his work asks how AI can meaningfully support architectural and planning practice without displacing professional responsibility, public deliberation, or local knowledge.
Alongside his academic work, Jonathan has founded several technology initiatives and co-founded Meirim, a platform promoting democratic participation in urban planning in Israel.
Projects
Education
- Ph.D. Tel Aviv University 2017 – 2021
- M.A. Tel Aviv University 2013 – 2017
- B. Arch. Tel Aviv University 2002 – 2008
Employment
- Postdoctoral fellow Technion Israel Institute of Technology Feb 2021 – Sep 2022
- Adjunct Teacher Technion Israel Institute of Technology 2019-09 – Oct 2021
- The School of Architecture Ariel University – Present
Papers
Few-Shot Transfer Learning for Cross-City Pedestrian Level-of-Service Mapping Using Spatio-Temporal Graph Models
Challenges in the Evaluation of Machine Learning Techniques in Generative Urban Design
The changing role of diagrams in architectural publications: From creative to communicative
Addressing Religious Architectural Restrictions with Computer Code: A Genetic Algorithm Approach
AI-Driven Recommendations for Strategic Urban Renewal
Quantifying Architectural Experience using VLMs: Does AI Dream of Rendered Spaces?
Towards a Robust Evaluation Framework for Generative Urban Design
When design workshops meet chatbots: Meaningful participation at scale?
Evaluating large-language-model chatbots to engage communities in large-scale design projects
Think AI-side the Box! Exploring the Usability of Text-to-Image Generators for Architecture Students
Conceptual Architectural Design at Scale: A Case Study of Community Participation Using Crowdsourcing
Poster: CHATBOTS IN THE DESIGN PROCESS - Automating Design Conversation in Urban Design Projects
A machine learning approach to urban design interventions in non-planned settlements
Toward a Generative Pipeline for an AR Tour of Contested Heritage Sites
Of Stones and Words - Computational Framework for Multifaceted Historical Narration of Wadi Salib
Collective Intelligence in Design Crowdsourcing
A Crowdsourcing Method for Architecture - Towards a Collaborative and Participatory Architectural Design Praxis
A Novel Crowdsourcing-based Approach for Collaborative Architectural Design
Open-source architecture and questions of intellectual property, tacit knowledge and liability
Open Source Architecture : Challenges and opportunities
Want to solve real urban problems with AI?
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