Exploring Challenges and Opportunities to Support Designers in Learning to Co-create with AI-based Manufacturing Design Tools

Human ExperiencesComputational Design
Written By Lining Yao

Frederic Gmeiner, Humphrey Yang, Lining Yao, Kenneth Holstein, and Nikolas Martelaro. The ACM CHI Conference on Human Factors in Computing Systems (CHI). 2023. PDF | DOI

Figure: The SimuLearn design task. (A) The user is prompted to design a bike bottle holder using the provided (B) starter file
and (C) the SimuLearn tool to create (D) morphing grid structures. (E) The transformed grid should assemble into the holder
and fit around the bottle and bike frame. (F) The SimuLearn tool provides three types of design workflows. After initializing a
morphing grid design, the user can choose between AI-assisted optimization functions or rapid simulations to iterate the design.

Lining Yao
Previous

Toward Fully Printed Soft Actuators: UV-Assisted Printing of Liquid Crystal Elastomers and Biphasic Liquid Metal Conductors
Next

Fluidic Computation Kit: Towards Electronic-free Shape-changing Interfaces