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Sofia Pia Belenky

Non-Extractive Architecture : On Designing without Depletion

bio:

Sofia Pia Belenky is a designer from New York currently based in Milan, Italy. She completed her BFA at Bard College in 2011 and continued her studies at the Graduate School of Architecture, Planning and Preservation at Columbia University, the Architectural Association and Strelka Institute. Sofia Pia works as a researcher and designer with Space Caviar, and previously collaborated with a number of offices in New York, London, and Paris. Her work with Space Caviar uses research, built work, writing, film, event, and exhibition design as forms of an extended mode of architectural practice.

Abstract

Non-Extractive Architecture is a live research platform focused on rethinking the balance between the built and natural environments, the role of technology and politics in future material economies, and the responsibility of the architect as an agent of transformation. The project sets out to examine — and redefine — the public’s expectations of the architect and architects’ expectations of themselves. What if architecture were understood first and foremost as a form of stewardship of the built and natural environments? What if we redesigned our economies to favour integration, circularity durability and social resilience through the towns and cities we build? What if the material supply chains behind environments we inhabit were visible and participatory rather than invisible and often exploitative? Non-Extractive Architecture engages individuals within and outside the field of architecture to create an open platform through which the current role of architecture can be debated, and new paths can be defined to leverage its potential as a positive force in shaping the future of the landscape.

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Speaker's bio:

Rupali Gupte is an architect and urbanist based in Mumbai. She is a co-founder of and Professor at the School of Environment and Architecture (SEA) and a partner at Bard Studio. Her work involves extensive research on contemporary South Asian architecture and urbanism with a focus on housing and urban form, tactical spatial practices, and the role of gender in shaping habitation. Her work often crosses disciplinary boundaries and takes different forms - writings, drawings, mixed-media works, installations, curation, conversations, walks and spatial interventions. Her works have been shown at 56th Venice Art Biennale, X Sao Paolo Biennale of Art and Architecture, Seoul Biennale of Art and Architecture, and at MACBA, Barcelona, MAAT Museum, Lisbon, Devi Art Foundation, Delhi, Mumbai Art Room, and Project 88, Mumbai.

Marc Timme, Chair for Network Dynamics, TU Dresden

http://networkdynamics.info

Inverse problems have a long history in the natural sciences and mathematics and are implicit to many engineering problems. For instance, Bragg diffraction techniques yield lattice spacings of periodic crystal lattices and design and closed-loop control schemes enable the reliable functioning of engineered machines near set operating points. Yet, for multi-dimensional systems the vast majority of research on collective nonlinear dynamics is still focusing on the “forward direction” of analysis or modeling and asks what types of collective dynamics emerge from a network of given units interacting via a given topology. How to infer features of systems that both are multi-dimensional and exhibit self-organized dynamics thus remains an open problem. Here we address two basic questions on network inference. First, how to identify the number of dynamical variables in a multi-dimensional system from observing time series of only some of them? Second, how to infer interaction topologies from recorded time series only, in particular without the knowledge of any specific model of the system? Both constitute partially uncharted territory for theory and may offer a wide range of applications. We also touch the dynamics of multi-dimensional mobility systems that pose even harder inference problems due to little data available and simultaneously complex, externally driven dynamics.

Example References:

[1] Theory of topology inference: Science Adv. 3: e1600396 (2017) and Nature Comm. 8:2192 (2017).

[2] Theory of system size inference: Phys. Rev. Lett. 122:158301 (2018).

[3] Constraining features of mobility systems: Nature Comm. 11: 4831 (2020) and Nature Comm. 12: 3003 (2021).

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The Autocene

The outcomes of the 20th Century ‘auto-motive complex’--individualistic autonomy, autopoetic infrastructure development, and automatic proliferation--are in many ways repeating today in the trajectories of autonomous vehicle development. In other ways, the logics and dynamics that enabled this planetary mobility are being reorganized by the expansion of platform automation. This talk frames this legacy as "the Autocene," an era that predates and may well surpass the Anthropocene, from the perspective of machine steerage. It reviews the legacies of platform automobility, prompting a more expansive rethinking of how past precedents shape the intelligent design and distribution of the Autocene to come.

Bio

Stephanie Sherman is a London-based director, producer, writer, and strategis working across design, urbanism, technology, and culture. She teaches City Design at the Royal College of Art, produces online radio broadcasts with Radioee.net, and collaborates on urban ecosystem projects with the think tank Autonomy UK, The UC San Diego Design Lab, and The UC Center for Design and Geopolitics. Stephanie is finalizing a PhD in Design at University of California San Diego. She holds an MA in Philosophy from Duke University and a BA in Literature from UPenn. http://stephaniesherman.net

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Open Lecture by Michael Szell "Vulnerable road user safety in Europe, and towards a science of bicycle network design"
May 6th, 2021, 5pm-6pm CET
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Speaker bio:

Michael Szell is associate professor in Data Science at IT University of Copenhagen, and external faculty at the Complexity Science Hub Vienna. His research aims to quantify the patterns behind interlinked human behavior and human-built structures through mining large-scale data sets. At ITU he has co-founded the NEtwoRks, Data, and Society (NERDS) research group bringing together interdisciplinary researchers to focus on quantitative projects at the boundary of network science, data science, and computational social science.

github: https://github.com/mszell
twitter: https://twitter.com/mszll

Illustration of work

Michael follows an interdisciplinary approach drawing from data science and network science. His current focus is on sustainable urban mobility and data visualization. His recent and ongoing research includes data-driven strategies to grow bicycle networks, using tools from multilayer networks to assess multimodal transport infrastructure, and a call for human-centric urban data science. Previously he has also developed the award-winning massive multiplayer online game "Pardus", www.pardus.at, and several interactive data visualization platforms.

Short abstract

In this presentation I will discuss two research projects. One work was recently completed, on identifying urban features for vulnerable road user safety in Europe. In this work we build up a large-scale data set of urban road crashes and their participants from 24 cities in 5 European countries, and model the casualty matrices including road infrastructure characteristics and modal share distributions. We observe that cities with the highest rates of walking and cycling modal shares are the safest for the most vulnerable users, suggesting that policies aimed at increasing the modal share of walking and cycling are key to improve road safety for all road users. In our ongoing research we explore systematically scenarios of growing urban bicycle networks from scratch. Here we study the process of growing a graph triangulation between an arbitrary set of points of interest routed on a city’s existing street network. We run different variations of this growth process on 62 diverse cities, tested against a random null model, and find non-trivial developments of network indicators implying that to be successful in bicycle network planning, cities must invest 1) with the right growth strategy, and 2) boldly, to overcome short-term deficiencies until a critical mass of bicycle tracks has been built up.

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Open Lecture: Data-Driven Tools for Decision Makers in City Planning
March 18th, 2021, 5pm-6pm CET
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Driven by her passion for data and cities, Talia Kaufmann is pursuing a PhD in Public Policy and is a Resident doctoral fellow at the Network Science Institute at Northeastern University. As part of her research, Talia collaborates with International organizations, local and municipal governments to develop data-driven tools for decision-makers in city planning. Her goal is to illuminate spatial inequality in access to services and provide policy makers with the tools to improve the quality of life of underserved urban communities. Her research tackles questions such as: how many commercial/recreational/public amenities should be added to a given neighborhood or city and where should those amenities be most needed? And, how far should an urban resident walk/drive/take public transport rides to reach the closest park or supermarket from their home?

Talia is trained as an Architect (B.Arch, Tel-Aviv University) and a City Planner (MCP, MIT). Before joining MIT for her Master degree, Talia served as a city planner and a planning information manager at the Tel Aviv-Yafo City Planning Department in Israel. Her research got international recognition by institutions as the World Bank, the OECD, the Government of Israel and more. Talia has been collaborating with the OECD for the past 3 years. She worked closely with the urban indicators team at the organization during summer and fall 2018 as an experiential fellow in Paris, France. At the OECD, Talia wrote a report titled ‘Measuring accessibility to services across cities: A framework for accessibility indicators by walking, driving and public transport’. The report demonstrated the potential of using Google’s fine-grained amenity data for accessibility indicators and was presented at the OECD Workshop on Modernising Statistical Systems for Better Data on Regions and Cities. Talia continues to work with the OECD to expand this framework to all oecd countries, expand it to measure the demand for amenities by measuring spatial consumption patterns and produce indicators for decision-makers.

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