Ongoing Research
Lead: Yoon Han
Computational Tomography of Spatial Dynamics
2016 –
Current research investigates a formal method to reintroduce spatial aspects into digital design processes. A computational framework is proposed that adopts the idea of space as dynamic field conditions, systemising tacit knowledge that has been considered as architectural sensibility for architects designing space as well as for users experiencing architectural space.
Lead: Oldouz Moslemian
Kinetic Textiles
2016 –
Textiles are a versatile material system based on patterns of woven interaction. Control of the interaction pattern enables a purposeful manipulation of the properties of the textile. This research investigates the implementation of material information in computational design processes and explores the potentials of digital tools within the realm of textile design.
Lead: Fangjie Xie
Principles of Structural Form
2017 –
This research explores the role of structural design as an architectural element and formal expression in contemporary Finnish architecture. Focus in the exploration is on modern Finnish church architecture and especially the work of Alvar Aalto and Juha Leiviskä.
Lead: Kane Borg
Rule generation from user design activity using machine learning
2018 –
The research aims at strategies to store and aggregate transcriptions of design activity and to develop methods leveraging this data for machine-human co-design application. The main goal is the development of a methodology and accompanying computational framework for formal transcription and aggregation of design knowledge in the industry for the augmentation of design processes.
Lead: Luka Piškorec
Deep Form Finding
2018 –
This research is exploring design methodology for the generation, manipulation, and form-finding of structural typologies in 3d using various machine learning models based on neural networks. Such generative neural network models have a large potential to redefine how architects work with architectural precedents and how to use them directly as data for design generation.
Lead: Tigran Khachatryan
Form – Formation – Information
2019 –
In a computational design approach, the formation process is the main carrier of information. The research explores the changing role of geometry in the transformation of information into a form that is in the encoding and decoding of data into a spatial configuration.
Lead: Desmond Fagan
Explainability of Deep Learning‐Based Decision
Support Systems
2021 –
The application of Decision Support Systems to software user interfaces has risen steadily in recent years. But the blackbox character of many of these applications limits the use of them in the AEC sector due to the perception of these interfaces as being opaque and untrustworthy. This research investigates methods of explainability to overcome the intransparent processing of data.
Lead: Sichen Dong
The tectonic performance of LVL-timber structure
2022 –
With respect of the need for sustainable development and circular economy, wood is of increasing importance for architecture. Especially industrial wood like laminated veneer lumber (LVL) offers much greater geometric flexibility. With LVL the focus moves away from the single element towards the organisational pattern of the overall configuration and its connectivity. This allows for new structural development and expression of roof design. This research aims at the exploration of the tectonic performance of LVL within an interdisciplinary setting between architecture and engineering.