Ongoing Research

3d Printing of Clay

2016 –

Lead: Ashish Mohite

This project is directed towards devising a methodology to use a 3D printer as a generative constituent of the design process. Grounded in a series of experimentations it is argued that the manipulation of manufacturing parameters could lead various architectural facets to be informed by the process of making.


Kinetic Textiles

2016 –

Lead: Oldouz Moslemian

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.


Computational Tomography of Spatial Dynamics

2016 –

Lead: Yoon Han

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.


Principles of Structural Form

2017 –

Lead: Fangjie Xie

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 Juha Leiviskä.


Rule generation from user design activity using machine learning

2018 –

Lead: Kane Borg

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.


Deep Form Finding

2018 –

Lead: Luka Piškorec

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.


Form – Formation – Information

2019 –

Lead: Tigran Khachatryan

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.


Mind in Structure

2019 –

Lead: Shuaizhong Wang

Taking structural design as a way of thinking, not just the material operations that uphold the building. This research starts with the notion of “Strong Structures”, and using graphic statics as an operational medium to link the neuroscientific and psychological human perception principles with mechanical principles, trying to introduce an embodied structural design thinking that could connect structure, space, and body.