UrbanGenetics: Adaptive Morphologies
GENERATIVE STUDY OF URBAN SCALE MULTI-PERFORMANCE THROUGH FORM
Seminar Faculty: Oana Taut
The XXI century is marking important changes in the evolution of urban environments. The first decade sealed the trend of consistent urban population growth by tipping-off, for the first time ever, the balance of population towards the urban. In the second decade we reached a singularity moment that is still untangling and causing important changes in our global and urban systems. Adding to these complexities, mass population displacement due to conflict or politics, is reaching a tipping point of visibility and acuteness. No doubt an accelerated process of development and renewal of urban structures is emerging in response to these conditions.
Credits: IAAC | Students: Sachin Dabas and Pedro Ribeiro; faculty: Gabriella Rossi and Iliana Papadopoulou
At the same time, urban planners, developers and AEC professionals are embracing digital technology and AI as solutions to the need for efficient decision making support. In this context, we are challenged with designing workflows and processes that bridge the complex, often divergent aims of the stakeholders affecting urban change.
This seminar focuses on equipping students with the frameworks and tools involved in applying advanced computational strategies at the urban scale. The goal is to achieve pragmatic solutions to the problems posed by urban development today, through generative explorations of well established formal typologies.
Rooted in the principles of evolutionary science, Genetic Optimization Algorithms promise to be a reliable problem solving method through search and optimization of multiple trade-off solutions. In recent years, Evolutionary Algorithms have gained increasing popularity to the point of becoming commonplace in certain subsets of the AEC field. In a speculative context, a wide variety of problems have been approached through the use of evolutionary solvers and results that appear to exceed human imagination have been received with applause. However, when proposing this method as the solution to large-scale complex real world problems, it is our responsibility as researchers to gain agency over the algorithm and confidently curate and qualify the raw output into coherent results.
Students will dedicate equal focus to: creating robust algorithms to generate urban form, defining pragmatic and complex goals for optimization, and evaluating, sorting and challenging the raw output of the evolutionary search.
Credits: IAAC | Students: Adriana Aguirre Such, Alvaro Cerezo Carrizo, Iñigo Esteban Marina, Tugdual Sarazin; Faculty: Milad Showkatbakhsh
Learning Objectives
At course completion the student will:
- Learn to identify and deconstruct urban form typologies;
- Learn algorithmic strategies to construct targeted design space for urban massing explorations;
- Learn how to lead a scientific process of of form optimization;
- Be able to encode/decode data from geometry and create relevant dashboards to aid the decision making process.
Faculty
Oana Taut is a Romanian architect and computational designer specialised in the field of AI in architecture. She obtained a Master’s Degree in Advanced Architecture from the Institute for Advanced Architecture of Catalonia.
Oana is the founder of BuildFlow where she leads the research of generative optimization and generative AI models to help design of performant and creative architectural space.
Her overall professional aim is to design quality space based on objective data, and materialise it in a sustainable way. Her master thesis project developed in IAAC is a research on the topic of artificial intelligence as enabler of a renewed architectural process.
Oana is also leading the Future Cities studio in CIEE at IAAC.
Before becoming a computational architect and AI researcher, Oana had gained extensive professional experience working educational, residential, hospitality and master planning projects internationally.
buildflowai.com
oanataut.com
linkedin.com/in/oana-taut-84958020/