This workshop will explore how artificial intelligence is used to reconstruct biomedical microscopy data, emphasizing both the opportunities and the risks of these approaches. While AI has enabled remarkable advances in virtual staining, super-resolution, and image translation, biomedical imaging presents unique challenges that make hallucinations far more consequential than in other domains. A false structure...

This workshop will introduce the UCLA research community to the application of diffusion models for medical imaging problems, with a focus on MRI. Participants will learn both the fundamentals of diffusion and how it can be adapted to physics-constrained scenarios, such as k-space undersampling in MRI. Demonstrations will be given using publicly available datasets (e.g.,...

This workshop introduces core methods for generating high-quality meshes used in large-scale simulation, scientific computing, and computer graphics. We will explore how Voronoi tessellation and Delaunay triangulation form the foundation of modern meshing algorithms, how parallel computing enables scalable geometry processing, and how emerging learning-based approaches can learn to generate meshes directly from data. The...