DESIGN COMPUTING


This course is on the theory of computational design and its application. Latest design research, design computing methodologies will be discussed in the class. The objective of this course is to approach design process computationally. Unlike traditional ways of exploring forms with hands and pencils, this course offers a way to explore forms with data and rules. To do that, students will go through as follows:

  1. Data Collection: Collecting all kinds of data through sensors, user observation or even word semantics.
  2. Identifying Rules: Formulating design rules from the collected data to create reconstructable designs.
  3. Synthesizing Designs: Computing novel design alternatives that fulfill design rules.

This course can teach students how data-driven design can support their design thinking and creativity. Ultimately, students will create their own Platform to design computationally. Students will use Processing & Python to create designs computationally. Coding skills are not prerequisite to this course.


Selected Student Works

2018 Spring

Design Drawn by Coding
by Shin Jong Hoon

Pattern generating software

2018 Spring

Image-Based Nonogram Generator
by Hwiwon Chun

Nonogram generating software

2018 Spring

Platform Game Random Map Generation
by Eugene Tan


2017 Fall

Genetic Beats
by Simon Asp

Online Publication:
︎ https://becominghuman.ai/

2017 Fall

Thermal Optimization based Glass Curtainwall Facade Design
by Sangwon Lee

2017 Spring

Seoul Bike Data Visualization
by Hyunjoo Kang


2017 Spring

Shadonation
by Hanol Rim & Hyeonsun Jeon

2017 Spring

Design by Computer (Random Based Design Generator)
by Jason Thuer

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