Improving Human Performance and Workflows through Computational Design

Human-centered design (HCD) is ubiquitous, and a variety of principles and methodologies have been developed to guide the HCD process, each tailored to specific contexts or problems. In this dissertation, we explore how computational design techniques can enhance human performance and streamline workflows through two complementary perspectives on HCD. The first perspective adopts the designer's lens to study end-user performance in physical and immersive environments. This dissertation presents two works along this line: the first investigates how functional layout designers can identify opportunities to improve worker performance by optimizing workspace arrangements and workplans. The second examines how instructors (as designers) can utilize trainees' performance data to create more efficient and effective training experiences for them (as end-users) in virtual reality (VR) settings. The second perspective shifts focus to supporting designers themselves, treating them as end-users and helping them improve their own workflows and design processes. Two research projects pursue this direction: the first enhances the authoring workflow for motion graphics designers, while the second improves the playtesting experience for game designers and developers. Across all four research works, we leverages computational design techniques and machine learning models to simulate, evaluate, and optimize interactions, ultimately enhancing both human performance and design workflows.

Author

• Zhang, Yongqi

• Human-computer Interaction
• optimization
• Virtual Reality

Identifier

hdl:1920/15229

OAI identifier oai:identifier

oai:MARS:1920/15229