The poster session is taking place on 16th of April at 8pm along with the opening reception at the Loeb Library, Harvard GSD. Our sponsor Swissnex will also briefly present the data visualisation project ‘Data Canvas’ (see below).

Our Poster Presenters

Ali Farzaneh, Architectural Association London, UK
“Digital Genomes in Architecture”

The research proposes that data-structure found in complex systems in biology serve as a new model for dealing with data-structures in design. It constructs what is referred to as digital genomes. In many ways, a digital genome is a data-structure that has a series of instructions embedded within it. The genomes are capable of dealing with complex systems simply in how the instructions are sequenced through simple sets of instructions. This allows the model to adapt and respond to a range of data and evolve an object or system through feedback.

About the author: Ali Farzaneh is a PhD Candidate in Architectural Design, at the Architectural Association in London. He has worked at Coop Himmelb(l)au in Vienna and SOM in Washington DC. He is co-director of the AA Visiting School in Aarhus, Denmark and has taught architectural design at the University of Oklahoma.

Walter Langelaar, Victoria University of Wellington, Wellington, New Zealand
“ Explorations in Data Commodification” is a web application that allows people to visualize and license their Facebook data directly to marketers. After exporting it from Facebook and uploading it to, users can choose to license their anonymized data under private, fair use, or commercial licenses and effectively cut out the middle man. The project functions as an artist-run Internet startup producing projects to help individuals capitalize on their online monetary potential. Their intention is to correct the imbalance of power in markets where users have no control over the transactions made with their personal data. They have completed various artistic projects and interventions on social media like, Fame Game, Give Me My Data, and Web 2.0 Suicide Machine. The co-authors are Birgit Bachler, Walter Langelaar, Owen Mundy and Tim Schwartz.

About the author: Walter Langelaar is an artist and educator from the Netherlands, based in Wellington (nz). His work in media arts and design ranges from artistic videogame modification to critical reflections on Internet technology and culture, and his installations and collaborative online projects have been shown in numerous venues, galleries and festivals like Transmediale and CTM, Gogbot, WORM, DEAF, Ars Electronica, iMAL and Medialab Prado. Walter is a Lecturer in Media Design at Victoria University of Wellington’s School of Design, where he also supervises the Data.Mine postgraduate research cluster. He is an avid user and strong proponent of Open Source tools and methodology in his teaching and practice.

Yannis Orfanos, Research Associate, Harvard GSD
“Data from infrastructure systems in computational tools for the urban environment”

A framework for integrating data from urban infrastructure systems in computational tools for the urban environment. Such an organizational framework interrelates data from infrastructure systems and urban environment across scales. The data framework becomes a multidimensional set of quantified relations across the components of each infrastructure system, across different infrastructure systems, across demographics and spatial parameters, and across scales. The framework concerns the infrastructure systems of water, energy, food and solid waste while the approach on computation focuses on problem solving and goal oriented modelling. Practical applications regard the fields of data analytics, computational design, and data-driven city management.

About the author: Yannis is a Research Associate at Harvard GSD investigating sustainable infrastructure systems and healthier cities. His education includes a Diploma in Architectural Engineering, MPhil from NTUA, and MArch in architecture and urbanism from AA Design Research Lab. He holds professional experience as architect and planner in Athens, London, and Barcelona.

Keisuke Yoshida, NOMURA Co., Ltd., Mikiya Takei, Doctoral Candidate, Toyohashi University of Technology, and Shiro Matsushima, Prof., Toyohashi University of Technology
“Database-Assisted Volumetric Study Method -A Case Study by Extracting Fundamental Data Set of Japanese Small Houses-“

This research is to develop an effective spatial enumeration method evaluating possibilities of their feasible compositions with data analysis and stochastic search. Statistical analysis applies to the data set associate with space design. The data is fitted in the statistical model to generate meaningful random value that shows tendency of design. By utilizing the tendency, space configuration is set on arbitrary site. The novel approach may contribute to the increase in the amount of time and can be spared for the design work. In addition, this method may produce unexpected space configurations even if they are bound by the conventional thought.

About the authors: Keisuke Yoshida joined NOMURA Co.,Ltd. ,Tokyo ,Japan. He received Master of Engineering in architecture from Toyohashi University of Technology, Bachelors of Engineering in architecture from Kogakuin University. His master’s thesis was awarded First Prize in Tokyo Architecture Collection 2014 symposium, Tokyo, Japan. Mikiya Takei is a doctoral candidate at Toyohashi University of Technology, Japan, and just finished his research as a visiting researcher at the University of Stuttgart under prof. Achim Menges. His research interest includes kinetic architecture, human sensing, and design robotics. He holds Master and Bachelor of Engineering in architecture, both from Toyohashi University of Technology. Shiro Matsushima is an architect and professor of Toyohashi University of Technology, Japan, where he teaches architectural design. He holds doctor of design and master in architecture II from Harvard GSD and master and bachelor of engineering in architecture from Kyoto University. He is interested in designing things out of human motion.

Data Canvas

Data Canvas is a media network to promote public education around civic issues. Together, with a community spread across 7 cities and 3 continents, we have created a DIY environmental sensor network where we are measuring air quality, dust, light, sound, temperature, and humidity. The data is being collected to empower citizens with real-time information about their surroundings.