Matias del Campo
Matias del Campo is an architect, designer, and theorist, currently serving as Director of the MS ACT program (Architecture, Computational Technology) and as Associate Professor at the New York Institute of Technology (NYIT). He co-founded SPAN in Vienna in 2003 with Sandra Manninger, establishing a practice renowned for its integration of contemporary technologies in architectural production. SPAN's award-winning designs are shaped by the intersection of computational methodologies and philosophical interrogations, a conceptual framework they describe as "design ecology." Matias del Campo's innovative contributions have been recognized through prestigious awards, including the Accelerate@CERN fellowship, the AIA Studio Prize and the ACADIA Innovative Research Award of Excellence. His work is included in the permanent collections of notable institutions such as the FRAC, the MAK in Vienna, the Benetton Collection, the Pinakothek Munich and the Albertina. He has authored several books on AI and Architecture such as “Neural Architecture” (ORO), “Diffusions” (Wiley), “Machine Hallucinations” (Wiley) and “Artificial Intelligence and Architecture” (Wiley).
Supervisors: Hans Hollein, Wolf D. Prix, Greg Lynn, Zaha Hadid, and Helmut Richter
Phone: 12672980608
Address: Edward Guiliano Global Center, 11th floor
1855 Broadway
Supervisors: Hans Hollein, Wolf D. Prix, Greg Lynn, Zaha Hadid, and Helmut Richter
Phone: 12672980608
Address: Edward Guiliano Global Center, 11th floor
1855 Broadway
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Videos by Matias del Campo
Can AI’s learn how to design?
This video contains excerpts of work by the artists: Mario Klingemann, Oscar Martinez and Obvious.
Images:
SPAN (Matias del Campo & Sandra Manninger), Alexandra Carlson, James Le, MIT Technology Review, Ersnt & Sohn Verlag, British Museum, Molly Wright Steenson, Facebook Intelligence Research Unit, Google Deepmind Alphago, Tesla, Xiachon Luo & Heng Li (Smart COnstruction Lab, Hong Kong Polytechnic University), Microsoft, PwC, RIB ITWO, John Deere, Hannah Daugherty, Mariana Moreira de Carvalho, Imman Suleiman, Karel Mestdagh, Leon A Gatys, Alexander S. Ecker, Matthias Betghe, Horoharu Kato, Yoshitaka Ushik
The motivation to explore Attention Generative Adversarial Networks (AttnGAN) as a design technique in architecture can be found in the desire to interrogate an alternative design methodology that does not rely on images as starting point for architecture design, but language. Traditionally architecture design relies on visual language to initiate as design process, wither this be a napkin sketch or a quick doodle in a 3D modeling environment. AttnGAN explores the information space present in programmatic needs, expressed in written form, and transforms them into a visual output. This visual output can be further processed into three dimensional models that transport lingual information into fully developed architectural entities. The key results of this research are shown in this paper with a proof-of-concept project: the competition entry for the 24 Highschool in Shenzhen, China. This award-winning project demonstrated the ability of AttnGAN
#artificialintelligence #architecture #design #agency #authorship #MachineLearning #neuralnetworks #posthuman #postdigital #lecture #ArtificialNeuralNetworks #theory #AttnGAN #caadria2021 #estrangement #defamiliarization #realism #ontology #aesthetics #prediction
Papers by Matias del Campo
By integrating humanities with computational tools, AI aids in crafting inclusive urban environments while enhancing real-time adaptability. Historic paradigms, from Renaissance precision to Modernist austerity, provide a foundation for understanding contemporary challenges. Modern AI techniques, such as data mining and generative design, allow designers to reimagine urban spaces while balancing ethical considerations like fairness and equity. This synergy of historical depth and computational advancement heralds a new era in urban design, characterized by both innovation and responsibility.
on urban design, transcending traditional paradigms and ushering in a new era
of data‑driven, generative approaches. Departing from linear processes, the text
embraces a comprehensive perspective, acknowledging the multidimensional factors shaping urban landscapes. The integration of AI in urban design takes cues
from how neural networks operate, dynamically responding to real‑time data
inputs and historical iterations. Historical reference points, from Renaissance
ideal cities to Modernism, serve as repositories guiding the interrogation of urban morphology.
The reasoning behind the text navigates the complexities of urban planning,
emphasizing the role of humanities in crafting inclusive, meaningful designs. The
interrogation delves into the historical intricacies, from Alberti’s Ideal City to
Simmel’s analysis of metropolitan existence, while scrutinizing modernist movements like Dada, cubism, and futurism and contrasting them with antiurban
ideologies in the works of Howard, Taut, and Wright.
This chapter then transitions to the contemporary landscape, portraying AI’s
disruptive moment in art and design. Drawing parallels with the modernist explosion, it discusses the dichotomy between organic, hands‑on creation and
AI‑driven, data‑informed methodologies. The tension between technological
precision and human creativity is explored, cautioning against the risk of detach
ing art from visceral experiences.
The integration of AI in urban design is examined, emphasizing its potential
in prediction, optimization, and generative design. AI’s capacity to process vast
amounts of data is highlighted, offering evidence‑based insights and breaking
free from traditional design molds. This chapter concludes by underscoring the
ethical considerations of AI in urban design, emphasizing the need for human intuition to complement computational insights and safeguard principles of equity
and social justice.
Can AI’s learn how to design?
This video contains excerpts of work by the artists: Mario Klingemann, Oscar Martinez and Obvious.
Images:
SPAN (Matias del Campo & Sandra Manninger), Alexandra Carlson, James Le, MIT Technology Review, Ersnt & Sohn Verlag, British Museum, Molly Wright Steenson, Facebook Intelligence Research Unit, Google Deepmind Alphago, Tesla, Xiachon Luo & Heng Li (Smart COnstruction Lab, Hong Kong Polytechnic University), Microsoft, PwC, RIB ITWO, John Deere, Hannah Daugherty, Mariana Moreira de Carvalho, Imman Suleiman, Karel Mestdagh, Leon A Gatys, Alexander S. Ecker, Matthias Betghe, Horoharu Kato, Yoshitaka Ushik
The motivation to explore Attention Generative Adversarial Networks (AttnGAN) as a design technique in architecture can be found in the desire to interrogate an alternative design methodology that does not rely on images as starting point for architecture design, but language. Traditionally architecture design relies on visual language to initiate as design process, wither this be a napkin sketch or a quick doodle in a 3D modeling environment. AttnGAN explores the information space present in programmatic needs, expressed in written form, and transforms them into a visual output. This visual output can be further processed into three dimensional models that transport lingual information into fully developed architectural entities. The key results of this research are shown in this paper with a proof-of-concept project: the competition entry for the 24 Highschool in Shenzhen, China. This award-winning project demonstrated the ability of AttnGAN
#artificialintelligence #architecture #design #agency #authorship #MachineLearning #neuralnetworks #posthuman #postdigital #lecture #ArtificialNeuralNetworks #theory #AttnGAN #caadria2021 #estrangement #defamiliarization #realism #ontology #aesthetics #prediction
By integrating humanities with computational tools, AI aids in crafting inclusive urban environments while enhancing real-time adaptability. Historic paradigms, from Renaissance precision to Modernist austerity, provide a foundation for understanding contemporary challenges. Modern AI techniques, such as data mining and generative design, allow designers to reimagine urban spaces while balancing ethical considerations like fairness and equity. This synergy of historical depth and computational advancement heralds a new era in urban design, characterized by both innovation and responsibility.
on urban design, transcending traditional paradigms and ushering in a new era
of data‑driven, generative approaches. Departing from linear processes, the text
embraces a comprehensive perspective, acknowledging the multidimensional factors shaping urban landscapes. The integration of AI in urban design takes cues
from how neural networks operate, dynamically responding to real‑time data
inputs and historical iterations. Historical reference points, from Renaissance
ideal cities to Modernism, serve as repositories guiding the interrogation of urban morphology.
The reasoning behind the text navigates the complexities of urban planning,
emphasizing the role of humanities in crafting inclusive, meaningful designs. The
interrogation delves into the historical intricacies, from Alberti’s Ideal City to
Simmel’s analysis of metropolitan existence, while scrutinizing modernist movements like Dada, cubism, and futurism and contrasting them with antiurban
ideologies in the works of Howard, Taut, and Wright.
This chapter then transitions to the contemporary landscape, portraying AI’s
disruptive moment in art and design. Drawing parallels with the modernist explosion, it discusses the dichotomy between organic, hands‑on creation and
AI‑driven, data‑informed methodologies. The tension between technological
precision and human creativity is explored, cautioning against the risk of detach
ing art from visceral experiences.
The integration of AI in urban design is examined, emphasizing its potential
in prediction, optimization, and generative design. AI’s capacity to process vast
amounts of data is highlighted, offering evidence‑based insights and breaking
free from traditional design molds. This chapter concludes by underscoring the
ethical considerations of AI in urban design, emphasizing the need for human intuition to complement computational insights and safeguard principles of equity
and social justice.
examination of the work of my practice SPAN. The text interrogates
how design research serves as a main tool for the development of novel
trajectories in the practice. This scene is set in this document by the
description of two main design approaches through a series of projects, the top down design technique of topological modelling and its application in a series of projects, and the subsequent transformation into a primarily bottom up technique, through the use of recursive algorithms and the exploration of emergent fabrication methods. The text examines how a design research went full circle - from an abstract machine (see p.180),-an object containing the opportunities to be interpreted as a series of projects through projects in an intermediate scale (Exhibition Designs, see p.143 - 178) to the scale of a building In what can be described as a plot-twist, the basic design technique of curvilinear, continuous spaces consisting of smooth single surfaces (see, Austrian Pavilion, p. 202-228) was abandoned in favour of a high resolution, intricate object condition with a clear tendency towards a granular component assembly that embraces the main architectural problems of joints, mullions, doors, arches, columns, fenestrations and corner problems (see for example, ORE, Shanghai Fashion Week Pavilions, p.229-234) .
This change allowed to discuss the projects considering the long trajectories of the architectural discipline. However, in contrast to the examples that exercise full control in a top down design process, Autonomous Tectonics speculates on the aspect of a non-anthropocentric design environment, where the architect as
the sole genius of a design is perceived as suspicious figure, and ideas
of full automation in design are embraced as an alternative creative
environment. This alternative method of design opens opportunities
to discuss aspects of a Postdigital world, of the impact of automation
to society, economy and culture, as well as providing alternative
morphologies, typologies and organizations of space.
A novel cultural entity that discusses moments of estrangement, the culture of the familiar vs the unfamiliar, the morphological language of big data, the sensibilities of AI’s and seeks a conversation on the aspects of architecture that possesses disciplinary autonomy, but is simultaneously embedded in the currents of a changing culture of production in which Autonomous Tectonics will be at play. This novel cultural entity is shared with a series of colleagues and peers who work on related conditions. People like Hernan Diaz Alonso, Francois Roche, Roland Snooks, Ezio Blassetti and Danielle Williams, Alisa Andrasek, Nicolo Cassas and more. This dissertation is an attempt to discuss the evolution of the work of SPAN through the lens of discoursive inquiry and cultural agency, resulting in the concept of Autonomous Tectonics.
In contrast to my partner, Sandra Manninger, who’s contribution to
discourse, deals with the aspects of geometry in SPAN’s body of work,
this dissertation is primarily concerned with aspects of materialization
and the affect produced through instances and artifacts of fabrication.
All of this is accompanied by the critical interrogation of the ontological
and epistemological framework emerging from the becoming of these
objects. Philosophy, in this frame of thinking (see p.240 - 266) serves as a source of inspiration and forms the base for the creation of a language to describe the projects inherent qualities. As Ludwig Wittgenstein famously said: What you cannot talk about, you have to remain silent about. For me this was never a proposition to remain silent, but a challenge to develop -and even invent- a language to describe and talk about my projects.