Papers by Maya Przybylski
Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA)
106th ACSA Annual Meeting Proceedings, The Ethical Imperative, 2018
Architecture and the Smart City, 2019
System Stalker Lab (SSL) is an introductory exploration of design computing, aiming to instill aw... more System Stalker Lab (SSL) is an introductory exploration of design computing, aiming to instill awareness of the structures, processes, and opportunities necessary to develop a design practice inclusive of computational strategies and techniques. SSL is offered as a third year undergraduate option studio at the School of Architecture at the University of Waterloo. The students participating in the studio are self-selected and enjoy a favorable class size of around twenty students, allowing for an intensive, focused semester. It is assumed that students coming into the studio do not have any computer code writing or reading experience.
INTRODUCTION Contemporary definitions of ecology foreground the importance of natural processes, ... more INTRODUCTION Contemporary definitions of ecology foreground the importance of natural processes, defining the discipline as the study of “patterns and processes influencing the distribution of organisms, the interactions among organisms, and the interactions between organisms and the transformation and flux of energy, matter and information”.1 With such a definition in mind, a growing body of work acknowledges lessons acquired from ecological science, presenting natural systems as dynamic, interconnected, resilient, complex and indeterminate, and attempts to situate strategies for design within this flux. In particular, the discourse surrounding Landscape Urbanism proposes that design should not set itself in opposition to such natural processes but instead be, in and of itself, inclusive and responsive by operating on principles of synthesis and encouraging hybridity across natural and engineered systems.
The Petropolis of Tomorrow, 2013
Studio briefs, influenced by an expansive view of architectural practice are increasingly foregro... more Studio briefs, influenced by an expansive view of architectural practice are increasingly foregrounding the architectural problem as inter-related, dynamic, and complex. Such a position is often focused on exposing patterns and processes as key drivers in a project. Sometimes this affects design projects in directly formal ways, and other times, these forces manifest in operational strategies. The discourse and studio projects surrounding Landscape Urbanism, which advocates a design practice wherein the project is seen to both affect and be affected by an inclusive set of environmental, social and economic factors, is an example of this. Through the lens of such a systems-based approach, the site is foregrounded as being dynamic, interconnected, resilient and indeterminate, and strategies for design within this flux are sought out.
How can we directly confront some of these qualities around complexity in early design? How can we foster the development of new methodologies and introduce new tools to beginning designers to incrementally build the capacity to confront complexity in design projects?
One approach, discussed here, involves coupling the learning around the systems-based design approach suggested above with another highly in-demand curricular component – that of design computation. Like its parent discipline of computation and other trans-disciplinary appropriations (such as computational ecology, computational economics etc.), design computation inherently presents strategies for managing complexity. However, within the academy, design computation is often presented, by way of workshops or elective courses, as a platform-specific skill highlighting the use of a computational tool (such as Grasshopper) to solve a suite of predetermined exercises. Recognizing that the field of design computation is changing and new applications for it are constantly emerging, it is opportune to explore ways to foreground the teaching of design computation not only as a specific tool or platform but as a methodology by which to approach design problem complexity in general.
System Stalker Lab, a third year undergraduate studio, introduces students to issues of complexity by way of an exploration of design computation. The studio incorporates key concepts from the discipline of Computer Science and draw parallels between it and design practice by unpacking cross-disciplinary notions of algorithmic thinking, representation, programming, and design. The studio sees the students engage with computation, enabling them to develop project-specific tools to structure their work as a dynamic system, and then explore the space of that system and develop it in an iterative manner to arrive at the final proposition. The studio exercises described here are designed to deliver the technical skills-based instruction required of design computation while, simultaneously, developing the students’ ability to confront, manage and respond to the complexity within a design problem.
An Interview with Michael U. Hensel
In recent years, practitioners and researchers in the fields of architecture, landscape architect... more In recent years, practitioners and researchers in the fields of architecture, landscape architecture and urban design have become increasingly interested in developing ecologically-informed design strategies. Within this setting, ecology is not simply a synonym for the environment, nor does it necessarily suggest a ‘green’ agenda; instead, it emphasizes a system-based holistic perspective of a given context. With such a definition in mind, a growing body of work acknowledges lessons acquired from ecological science, presenting natural systems as dynamic, interconnected, resilient, complex and indeterminate, and attempts to situate strategies for design within this flux. Yet, the tools and methods currently used by designers with which to advance such work are limited. The familiar practice of mapping, in formats such as spatial maps, timelines, organizational diagrams, and other modes of visualization, is the central driver currently used in presenting, synthesizing and mobilizing ecologically-oriented, systems-based design interventions. However, in most cases, such drivers are offered as-is, with little explication of their validity, assumptions and limits, and, as a result, are fundamentally bounded by the limits of ecological metaphor. Although metaphor is recognized as a useful communication tool across disciplines, there is a “rich technical world” that stands behind it; one which offers much opportunity to ecologically-informed design practice.
Surpassing the boundaries of ecological metaphor demands a set of tools which can deal with managing the dynamic processes and forces, flows and feedback loops, which characterize ecological systems. While current techniques are helpful in isolating and abstracting certain aspects of these ecosystems, much of their inherent complexity is lost due to our human limits in managing and working with complex, parallel relational chains. Herein rests an opportunity for computational design to appropriate ecological modeling, as a point of access to the full technical richness of ecological science. In this context, the computational designer is able to abstract a problem for initial action and then, relying on the machine as an automatic accountant, incrementally rebuild the lost complexity, thereby allowing the relevant characteristics of the problem space to be maintained.
An appropriation of ecological modeling into design practice offers a parametric and relational framework for advancing ecologically-informed design as a process of formation, which affords both generative and exploratory opportunities to the development of landscape infrastructure. Similarly, hybrid ecological models, which couple multi-disciplinary parameters and characteristics, offer a mechanism for simulating emergent ecological-urban possibility spaces, extending a designers ability to both navigate and cultivate epigenetic potentials, toward the formation of a synergistic territory where human-centered needs and ecosystem logics coexist to mutual benefit.
Such a vision need not be utopian; emerging thinking and investigation surrounding natural capital and ecosystem services suggest that market-driven metrics need not be left behind. Drawing on existing precedents around the world of such redirected agency, we can begin to speculate on a new future for the post-industrial city that resists simple categorization and advances a new language for emerging landscape potentials.
When the Ontario government defined the province’s Greenbelt in 2005, a second belt, known as the... more When the Ontario government defined the province’s Greenbelt in 2005, a second belt, known as the whitebelt, was also implicitly created. For the explicitly defined Greenbelt, future planning is relatively clear as development within its boundaries is highly controlled as preserving natural areas and agricultural lands are paramount. The greenbelt effectively demarcates a zone, wrapping loosely around the Greater Golden Horseshoe in southwestern Ontario, where urban development should not occur. For the resultant whitebelt, understood as the residual buffer zone between the new greenbelt boundary to its north and the already developed or planned-for developments to its south, the future is less clear. The incredible potentials of the whitebelt, both its ties to the greenbelt and its capacity for new development, are brought to the fore when seen from a shifted planning and design perspective. The urges to view the whitebelt as either some lighter, less-rigid version of the Greenbelt or as a placeholder for some future, status quo, development should both be resisted. Instead of positioning the whitebelt as a passive buffer zone, it is interesting to speculate how it becomes a radically reimagined landscape: a landscape where its neighbours (Greenbelt to the north and urban metropolitan area to the south) are not pitted against one another but instead leveraged together in creating a synergistic territory were human-centered needs and ecosystem logics coexist to mutual benefit. While some versions of such a future may rely on utopian visions, emerging thinking and design work surrounding ideas of natural capital and ecosystem-services, suggest that market-driven, capitalistic metrics need not be left behind. In examining existing examples around the world of such redirected agency through design, we can begin to speculate on a new future for areas within the GTHA that resist singular categorizations as either urban or rural, white or green – but expose a new language for the emerging landscape potentials.
This paper discusses work from System Stalker Lab, a third year undergraduate design studio taugh... more This paper discusses work from System Stalker Lab, a third year undergraduate design studio taught at the University of Waterloo. System Stalker Lab is an introductory exploration of design computing, aiming to instill awareness of the key structures and processes inherent in a design practice inclusive of computational strategies and techniques. The studio also seeks to seed a computationally oriented design culture within the school by clarifying and speculating on the opportunities existing within computing in relationship to architectural design. Such a practice requires that designers expand their notion of digital methodologies to include the fundamental paradigms of computer science. The focus of the paper is on the first phase of work carried out in the studio, which is committed to building a workable foundation in algorithmic thinking, representation, programming and design – core skills required for working within a computational context. The described process exposes students to the skills necessary for the conceptualization, design, and execution of a project operating within a computational discourse. Having completed the first, highly structured phase of the studio, students are enabled to continue to learn independently and to employ computational design in more open design projects.
Conference Presentations by Maya Przybylski
While the advent of digital media and tools has transformed the practice of architecture over the... more While the advent of digital media and tools has transformed the practice of architecture over the past several decades, the opportunities afforded by this revolution are only starting to be fully understood. A new abundance of data, unprecedented in quantity and breadth, presents the designer with multiple dimensions along which to analyze a given site. Social, cultural, environmental and geographic information is collected from more and more sources, and becoming increasingly collated and spatially indexed. Many architects and designers have recognized this new condition and have sought to grapple with it and represent it, generating a body of work that might loosely be called ‘systems-oriented’.
However, the techniques used to analyze such data, and to utilize the results in design decision-making, have by and large not kept pace. Often this gap can in part be attributed to the designers’ lack of ability to fully engage with digital techniques to develop custom digital tools tailored to the problem at hand. While use of digital tools in architecture is widespread, often these tools are simply digital versions of manual techniques. An interest in fully harnessing the rule-based intelligence of digital technology with application to design problems has been characterized as ‘design computation’.
The Soft Data | Hard Design research project seeks to explore the application of design computation to take full advantage of the abundance of data, with the goal of shaping and improving both the methodologies and the outcomes of the designer. The project operates across a range of scales and complexities from installation/building component, to building, to urban site, city, and region. While still in its early phases, Soft Data | Hard Design has yielded several research/creation experiments. A defining aspect of each of the projects is the recognition of complexity, prompting the experimental use of data processing and information visualization as a catalyst for design proposition. Traditional notions of mapping are expanded through spatial, temporal, visual and technical experiments. The project outlined below is one such example.
Next North Interactive Data Project
Next North is a research-creation project centered on examining the Canada’s North through a variety of lenses including ecology, transportation, resources, culture, and settlement. The project was carried out as a collaboration between InfraNet Lab and Lateral Office. The Next North exhibition, a culmination of this phase of research, merges documentation and projection (Image 1). Specific design propositions are complemented with a range of artifacts, such as maps, timelines, and installations to help contextualize these new visions of the North for the exhibition’s visitors.
A subcomponent of this larger project, The Interactive Data Project (IDP) was an interactive, web-based application designed to organize and share the research gathered during the Next North project. The goal of the IDP was to design a platform that could, on the one hand, support real-time sharing of research between a geographically dispersed team and, on the other hand, support the sharing of this work with the general public at the Next North exhibition.
At the core of the IDP lies an online database of research collected over the course of the Next North project. While geographically dispersed research groups were focusing on unique themes, such as housing and transportation, overlaps between findings and materials were inevitable. A centralized, searchable archive supported a collective effort in amassing research material while simultaneously minimizing duplication of effort.
During the exhibition, the IDP was presented as two complementary components, the interactive timeline and the research wall, each working to contextualize, for exhibition visitors, the formation of design strategies for the various presented architectural interventions (Image 2). The research wall was populated with data cards, each capturing existing spatial conditions characterizing the Canadian North. The cards were organized by project themes identified by colour. The research wall emphasized a curated, asynchronous view of the research work.
Complementing this fixed representation, the interactive timeline component emphasized a user-driven, synchronous, experience of the body of research. Streaming live content from the continually evolving online database throughout the show’s duration, the timeline was updated in real-time to capture the current state of the research project. Users were able to filter and sort research data according to theme and date. The ability to isolate related elements encouraged visitors to engage in each of the project themes more directly, to unpack how each contributes to our overall understanding of the North.
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Papers by Maya Przybylski
How can we directly confront some of these qualities around complexity in early design? How can we foster the development of new methodologies and introduce new tools to beginning designers to incrementally build the capacity to confront complexity in design projects?
One approach, discussed here, involves coupling the learning around the systems-based design approach suggested above with another highly in-demand curricular component – that of design computation. Like its parent discipline of computation and other trans-disciplinary appropriations (such as computational ecology, computational economics etc.), design computation inherently presents strategies for managing complexity. However, within the academy, design computation is often presented, by way of workshops or elective courses, as a platform-specific skill highlighting the use of a computational tool (such as Grasshopper) to solve a suite of predetermined exercises. Recognizing that the field of design computation is changing and new applications for it are constantly emerging, it is opportune to explore ways to foreground the teaching of design computation not only as a specific tool or platform but as a methodology by which to approach design problem complexity in general.
System Stalker Lab, a third year undergraduate studio, introduces students to issues of complexity by way of an exploration of design computation. The studio incorporates key concepts from the discipline of Computer Science and draw parallels between it and design practice by unpacking cross-disciplinary notions of algorithmic thinking, representation, programming, and design. The studio sees the students engage with computation, enabling them to develop project-specific tools to structure their work as a dynamic system, and then explore the space of that system and develop it in an iterative manner to arrive at the final proposition. The studio exercises described here are designed to deliver the technical skills-based instruction required of design computation while, simultaneously, developing the students’ ability to confront, manage and respond to the complexity within a design problem.
Surpassing the boundaries of ecological metaphor demands a set of tools which can deal with managing the dynamic processes and forces, flows and feedback loops, which characterize ecological systems. While current techniques are helpful in isolating and abstracting certain aspects of these ecosystems, much of their inherent complexity is lost due to our human limits in managing and working with complex, parallel relational chains. Herein rests an opportunity for computational design to appropriate ecological modeling, as a point of access to the full technical richness of ecological science. In this context, the computational designer is able to abstract a problem for initial action and then, relying on the machine as an automatic accountant, incrementally rebuild the lost complexity, thereby allowing the relevant characteristics of the problem space to be maintained.
An appropriation of ecological modeling into design practice offers a parametric and relational framework for advancing ecologically-informed design as a process of formation, which affords both generative and exploratory opportunities to the development of landscape infrastructure. Similarly, hybrid ecological models, which couple multi-disciplinary parameters and characteristics, offer a mechanism for simulating emergent ecological-urban possibility spaces, extending a designers ability to both navigate and cultivate epigenetic potentials, toward the formation of a synergistic territory where human-centered needs and ecosystem logics coexist to mutual benefit.
Such a vision need not be utopian; emerging thinking and investigation surrounding natural capital and ecosystem services suggest that market-driven metrics need not be left behind. Drawing on existing precedents around the world of such redirected agency, we can begin to speculate on a new future for the post-industrial city that resists simple categorization and advances a new language for emerging landscape potentials.
Conference Presentations by Maya Przybylski
However, the techniques used to analyze such data, and to utilize the results in design decision-making, have by and large not kept pace. Often this gap can in part be attributed to the designers’ lack of ability to fully engage with digital techniques to develop custom digital tools tailored to the problem at hand. While use of digital tools in architecture is widespread, often these tools are simply digital versions of manual techniques. An interest in fully harnessing the rule-based intelligence of digital technology with application to design problems has been characterized as ‘design computation’.
The Soft Data | Hard Design research project seeks to explore the application of design computation to take full advantage of the abundance of data, with the goal of shaping and improving both the methodologies and the outcomes of the designer. The project operates across a range of scales and complexities from installation/building component, to building, to urban site, city, and region. While still in its early phases, Soft Data | Hard Design has yielded several research/creation experiments. A defining aspect of each of the projects is the recognition of complexity, prompting the experimental use of data processing and information visualization as a catalyst for design proposition. Traditional notions of mapping are expanded through spatial, temporal, visual and technical experiments. The project outlined below is one such example.
Next North Interactive Data Project
Next North is a research-creation project centered on examining the Canada’s North through a variety of lenses including ecology, transportation, resources, culture, and settlement. The project was carried out as a collaboration between InfraNet Lab and Lateral Office. The Next North exhibition, a culmination of this phase of research, merges documentation and projection (Image 1). Specific design propositions are complemented with a range of artifacts, such as maps, timelines, and installations to help contextualize these new visions of the North for the exhibition’s visitors.
A subcomponent of this larger project, The Interactive Data Project (IDP) was an interactive, web-based application designed to organize and share the research gathered during the Next North project. The goal of the IDP was to design a platform that could, on the one hand, support real-time sharing of research between a geographically dispersed team and, on the other hand, support the sharing of this work with the general public at the Next North exhibition.
At the core of the IDP lies an online database of research collected over the course of the Next North project. While geographically dispersed research groups were focusing on unique themes, such as housing and transportation, overlaps between findings and materials were inevitable. A centralized, searchable archive supported a collective effort in amassing research material while simultaneously minimizing duplication of effort.
During the exhibition, the IDP was presented as two complementary components, the interactive timeline and the research wall, each working to contextualize, for exhibition visitors, the formation of design strategies for the various presented architectural interventions (Image 2). The research wall was populated with data cards, each capturing existing spatial conditions characterizing the Canadian North. The cards were organized by project themes identified by colour. The research wall emphasized a curated, asynchronous view of the research work.
Complementing this fixed representation, the interactive timeline component emphasized a user-driven, synchronous, experience of the body of research. Streaming live content from the continually evolving online database throughout the show’s duration, the timeline was updated in real-time to capture the current state of the research project. Users were able to filter and sort research data according to theme and date. The ability to isolate related elements encouraged visitors to engage in each of the project themes more directly, to unpack how each contributes to our overall understanding of the North.
How can we directly confront some of these qualities around complexity in early design? How can we foster the development of new methodologies and introduce new tools to beginning designers to incrementally build the capacity to confront complexity in design projects?
One approach, discussed here, involves coupling the learning around the systems-based design approach suggested above with another highly in-demand curricular component – that of design computation. Like its parent discipline of computation and other trans-disciplinary appropriations (such as computational ecology, computational economics etc.), design computation inherently presents strategies for managing complexity. However, within the academy, design computation is often presented, by way of workshops or elective courses, as a platform-specific skill highlighting the use of a computational tool (such as Grasshopper) to solve a suite of predetermined exercises. Recognizing that the field of design computation is changing and new applications for it are constantly emerging, it is opportune to explore ways to foreground the teaching of design computation not only as a specific tool or platform but as a methodology by which to approach design problem complexity in general.
System Stalker Lab, a third year undergraduate studio, introduces students to issues of complexity by way of an exploration of design computation. The studio incorporates key concepts from the discipline of Computer Science and draw parallels between it and design practice by unpacking cross-disciplinary notions of algorithmic thinking, representation, programming, and design. The studio sees the students engage with computation, enabling them to develop project-specific tools to structure their work as a dynamic system, and then explore the space of that system and develop it in an iterative manner to arrive at the final proposition. The studio exercises described here are designed to deliver the technical skills-based instruction required of design computation while, simultaneously, developing the students’ ability to confront, manage and respond to the complexity within a design problem.
Surpassing the boundaries of ecological metaphor demands a set of tools which can deal with managing the dynamic processes and forces, flows and feedback loops, which characterize ecological systems. While current techniques are helpful in isolating and abstracting certain aspects of these ecosystems, much of their inherent complexity is lost due to our human limits in managing and working with complex, parallel relational chains. Herein rests an opportunity for computational design to appropriate ecological modeling, as a point of access to the full technical richness of ecological science. In this context, the computational designer is able to abstract a problem for initial action and then, relying on the machine as an automatic accountant, incrementally rebuild the lost complexity, thereby allowing the relevant characteristics of the problem space to be maintained.
An appropriation of ecological modeling into design practice offers a parametric and relational framework for advancing ecologically-informed design as a process of formation, which affords both generative and exploratory opportunities to the development of landscape infrastructure. Similarly, hybrid ecological models, which couple multi-disciplinary parameters and characteristics, offer a mechanism for simulating emergent ecological-urban possibility spaces, extending a designers ability to both navigate and cultivate epigenetic potentials, toward the formation of a synergistic territory where human-centered needs and ecosystem logics coexist to mutual benefit.
Such a vision need not be utopian; emerging thinking and investigation surrounding natural capital and ecosystem services suggest that market-driven metrics need not be left behind. Drawing on existing precedents around the world of such redirected agency, we can begin to speculate on a new future for the post-industrial city that resists simple categorization and advances a new language for emerging landscape potentials.
However, the techniques used to analyze such data, and to utilize the results in design decision-making, have by and large not kept pace. Often this gap can in part be attributed to the designers’ lack of ability to fully engage with digital techniques to develop custom digital tools tailored to the problem at hand. While use of digital tools in architecture is widespread, often these tools are simply digital versions of manual techniques. An interest in fully harnessing the rule-based intelligence of digital technology with application to design problems has been characterized as ‘design computation’.
The Soft Data | Hard Design research project seeks to explore the application of design computation to take full advantage of the abundance of data, with the goal of shaping and improving both the methodologies and the outcomes of the designer. The project operates across a range of scales and complexities from installation/building component, to building, to urban site, city, and region. While still in its early phases, Soft Data | Hard Design has yielded several research/creation experiments. A defining aspect of each of the projects is the recognition of complexity, prompting the experimental use of data processing and information visualization as a catalyst for design proposition. Traditional notions of mapping are expanded through spatial, temporal, visual and technical experiments. The project outlined below is one such example.
Next North Interactive Data Project
Next North is a research-creation project centered on examining the Canada’s North through a variety of lenses including ecology, transportation, resources, culture, and settlement. The project was carried out as a collaboration between InfraNet Lab and Lateral Office. The Next North exhibition, a culmination of this phase of research, merges documentation and projection (Image 1). Specific design propositions are complemented with a range of artifacts, such as maps, timelines, and installations to help contextualize these new visions of the North for the exhibition’s visitors.
A subcomponent of this larger project, The Interactive Data Project (IDP) was an interactive, web-based application designed to organize and share the research gathered during the Next North project. The goal of the IDP was to design a platform that could, on the one hand, support real-time sharing of research between a geographically dispersed team and, on the other hand, support the sharing of this work with the general public at the Next North exhibition.
At the core of the IDP lies an online database of research collected over the course of the Next North project. While geographically dispersed research groups were focusing on unique themes, such as housing and transportation, overlaps between findings and materials were inevitable. A centralized, searchable archive supported a collective effort in amassing research material while simultaneously minimizing duplication of effort.
During the exhibition, the IDP was presented as two complementary components, the interactive timeline and the research wall, each working to contextualize, for exhibition visitors, the formation of design strategies for the various presented architectural interventions (Image 2). The research wall was populated with data cards, each capturing existing spatial conditions characterizing the Canadian North. The cards were organized by project themes identified by colour. The research wall emphasized a curated, asynchronous view of the research work.
Complementing this fixed representation, the interactive timeline component emphasized a user-driven, synchronous, experience of the body of research. Streaming live content from the continually evolving online database throughout the show’s duration, the timeline was updated in real-time to capture the current state of the research project. Users were able to filter and sort research data according to theme and date. The ability to isolate related elements encouraged visitors to engage in each of the project themes more directly, to unpack how each contributes to our overall understanding of the North.