Learning from Design Heritage
Research Workshop on Data-driven Methods
|Various digital methods used in a research project on Machu Picchu.|
This class investigates recent technologies that helps studying "design heritage", spatial designs that surround our lives. Design heritage broadly includes architecture, city and landscape; the built, demolished, and planned; and culturally important as well as the banal ones. We will look at various data-driven methods relevant to learn them, such as photogrammetry, image/video feature detection, machine learning, physiological sensors, natural language processing, augmented and virtual reality, and gamification. By examining how to collect data, how to process the raw data into forms useful for evaluation, and how to interpret and apply the findings, the students build a foundation for research projects bettering our understanding of the design heritage around us.
Each week during the first half of the class, the class will invite a guest speaker, conduct a short hands-on exercise on a data processing tool, and read relevant literature from previous research projects in design heritage. The second half is run in a workshop format with desk critiques, where students are expected to design and develop a small research project individually or in a group. There is no requirement for computational skills for this class, although familiarity with some scripting language is an advantage.
Takehiko Nagakura (firstname.lastname@example.org), Daniel Tsai and weekly guest speakers
TA: Charles Wu (email@example.com)
Regular Class Hours: Monday 11:00 AM - 2:00 PM (Rm 8-119)
Lab (subject to change): Tuesday, 7:00 PM - 8:30 PM (Rm 5-216)
* Lab hours are used for demos during the first half of the semester, and for project development by student teams during the second half.
* The final presentation of this class takes place during the last class just before the MIT exam week in May 2022.
Some of the following sections are under construction.