Brown Interactive 3D Vision and Learning Lab• Collected a large-scale, real-world 360◦ multi-view data set with 53 dynamic sequences to enable continued progress in dynamic radiance field research.• Evaluated dynamic neural field methods on image reconstruction quality for the data set to provide a benchmark for radiance field methods.• Developed a pipeline to automate custom data collection, camera calibration, and radiance field reconstruction.• Explored pose-estimation methods (AlphaPose, OpenPose, MediaPipe) to accurately extract 3D keypoints and joint angles of hands from multi-view images.

• Created and improved lab and project handouts, stencil code, and solution code to optimize student learning for the course's 2D Graphics and Realtime Graphics sections.• Tested, provided feedback, and refined handouts and stencil code to ensure clarity and conciseness in assignments.