4D is closer than you think: take any 3D structure, say a pipe system, and slap on a variable for pressure. Yet, most experts at all levels of academia often portray the visualization of 4D space as impossible, in large part because the most accessible learning aids require significant effort to understand. My project aims to address this by implementing a new model for representing 4D objects using level surfaces with varying transparency and color, allowing users to explore 4D space.

I’m working with Senior Computer Vision Engineer Dr. Yongxi Hou at NVIDIA to develop an interactive, dynamic display integrating existing wireframe techniques, as well as my new transparent level surfaces, to identify which requires the least reading and effort from the user to understand. I’m learning how to use the 3D transformation matrix, what potential tricks exist to simplify its 4D counterpart, and which Python libraries would make such a program run efficiently.

I will develop a quiz to investigate the accuracy with which students exposed to the previously mentioned models are able to identify transformations, rotations, and other geometrical operations, compared with how much additional reading is needed. The reading be increased from explaining what the model represents to a full lesson with 2D-3D analogies as the student progresses. With a stronger grasp of 4D space, students will develop the skills to understand abstract concepts with visual tricks I hope to integrate into classroom learning.