> AiDAPT Lab: TU Delft’s AI Lab for Design, Analysis, and Optimization

Faculty of Architecture & the Built Environment 

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Keywords

Artificial Intelligence, Optimization, Life-cycle Decision-Making, Design.

Initiated by

Charalampos Andriotis, Seyran Khademi

About

AiDAPT aims at developing AI methods able to support informed design decisions, through coupled data-driven and model-based approaches to the design-related optimization processes. Seeing design as an extended, multi-scale and dynamic life-cycle procedure, the two main research streams

 

AiDAPT pursues are:

- Dynamic learning and autonomous decision-making under uncertainty to enhance the life-cycle dimension of design. This includes reinforcement learning and deep learning methods, aiming at assisting architects and engineers to assess and control the long-term physics-driven responses of the built environment.
- Automatic recognition (classification, localization, matching, retrieval) and understanding (captioning, interpretation, summarization) the attributes of the visual data in various architectural representations and scales, aiming at assisting architects and engineers by providing relevant and interpretable visual analysis for the initial design process.

 

Overall, the developed frameworks will enable intelligent processes for abstraction and synthesis of structural and architectural decisions, ranging from the stage of initial design to future intervention and adaptation planning (e.g. maintenance, retrofits, form changes, etc.) and data collection scheduling. This integral approach will close the loop from data to design and vice versa, supporting adaptive and evidence-based choices for architects, civil engineers, designers, and policy-makers.

Funded by

TU Delft AI Labs Program

Contact

c.andriotis@tudelft.nl

s.khademi@tudelft.nl 

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