The emergence of text-to-image generative models (e.g., Midjourney, DALL-E 2, Stable Diffusion) in the summer of 2022 impacted architectural visual culture suddenly, severely, and seemingly out of nowhere. To contextualize this phenomenon, in an issue of The International Journal of Architectural Computing, I offer a socio-technical history of contemporary text-to-image generative systems.

In a chapter of Diffusions in Architecture - Artificial Intelligence and Image Generators, edited by Matias del Campo, I argue that in the context of prompt-based architectural visualization, designers must learn to navigate landscapes beyond the technical.

In a chapter of Artificial Intelligence and Architecture: From Research to Practice, edited by Stanislas Chaillou, I argue that while recent developments in artificial intelligence threaten to dislodge some of our basic assumptions about the nature and purpose of computational design tools, creative designers ought to welcome the disruption.

I was invited to contribute the first chapter of The Routledge Companion to Artificial Intelligence in Architecture, an edited volume that surveys the state of the art in Artificial Intelligence (AI) as it relates to architecture. In this chapter, I sketch out of a number of models for practice that I see emerging in the area of machine-augmented architectural design, each defined in terms of how it situates the use of ML in design differently.

This paper presents a technical account of the development of an the augmented architectural drawing tool Sketch2Pix: an interactive application that sup-ports architectural sketching augmented by automated image-to-image translation processes.

This paper documents the approach taken by and the work produced in an undergraduate research studio conducted at UC Berkeley in the Spring of 2020. Here, a series of small design projects examine the applicability of machine-augmented sketching tools to early-stage architectural design.

This paper presents a new prototyping visualization toolkit, developed for the Grasshopper (Rutten 2013) visual programming environment, which enables the situational development of information graphics.

This paper presents a framework for the application of Machine Learning (ML) to Generative Architectural Design (GAD), and illustrates this framework through a description of a series of projects completed at the Smart Geometry conference in May of 2018 (SG 2018) in Toronto.

This paper documents the process of developing a custom-built weather data parser, and producing a number of diagrams and data visualizations. These visualizations are not only useful in and of themselves for aligning design strategies to specific contexts, but they also illustrate the foundations of a larger theoretical framework for the processing and visualization of climatic data for effective utilization of bioclimatic flows.

This paper presents a web-based framework that enables the production of user-generated visualizations of weather data.

In the inargual issue of Room One Thousand, this essay advocates for designers to look deeper into the nested black boxes that comprise architectural software.

To demonstrate the how space architecture designers can create intelligent associative models, this paper presents an iterative method for refining the shell and interior design of a surface endoskeletal inflatable module.

In this introduction to an ACADIA conference session of the same name presents a new prototyping visualization toolkit, developed for the Grasshopper visual programming environment, which enables the situational development of information graphics.

This paper argues that prevailing approaches to CAD software have been fashioned to support modes of reasoning only of secondary importance to design activity, and that, due to some recent developments in computer vision, this state of affairs may be about to change. Surveying the current state of CAD tools, a critical position is developed based upon the best current understanding of the cognitive processes related to design.

This paper presents progress in the development of practical applications for graph representations of meshes for a variety of problems relevant to generative architectural design (GAD).

Given the widespread use of meshes and the utility of segmentation in generative architectural design, by surveying the relevant and recently matured approaches to mesh segmentation in CG that share a common representation of the mesh dual, this paper identifies and takes steps to address a heretofore unrealized transfer of technology that would resolve a missed opportunity for both subject areas.

In a chapter of the edited volume Paradigms in Computing, I present a framework for understanding a shift discernible in contemporary design culture. Here, I describe a shift from a nostalgic notion of direct authorship, understood as a compositional relationship between a designer and the product of his work, to a multiplicity of deferred authorships, wherein the stakeholders in the production of a design are mediated by systems of collaboration.

Geometric Computation: Foundations for Design describes the mathematical and computational concepts that are central to the practical application of design computation in a manner tailored to the visual designer. Uniquely pairing key topics in code and geometry, this book develops the two key faculties required by designers that seek to integrate computation into their creative practice: an understanding of the structure of code in object-oriented programming, and a proficiency in the fundamental geometric constructs that underlie much of the computational media in visual design.

Big Data has been effectively mined to understand behavioural patterns in cities and to map large-scale trends predicated upon the repeated actions of many aggregated individuals. While acknowledging the vital role that this work has played in harnessing the Urban Internet of Things as a means to ensure efficient and sustainable urban systems, our work seeks to recover a scale of behavioural research associated with earlier, empirical studies on urban networks.

This study applies a programmatic paradigm taxonomy to a comparison of two programming environments: Decodes and DesignScript, and yields a set of suggested guidelines for the context-appropriate application of each of these paradigms.

The nature of design tools is related to the social relationships they serve. This paper speculates on the emergence of a new professional configuration - the synthesis of architect and engineer - and on the nature of new computational tools and methods that will be required to support such a reconfiguration.

This paper presents three strategies – host-independence, domain-specificity, and context-appropriate abstraction – for the design of a textual programming environment supporting computational architectural design that more effectively addresses the needs implied by common practices within this community.