Alexander Ho

This paper introduces FPhaS, a framework for confidence-supported label-free metabolic imaging using phase autofluorescence microscopy, improving accuracy by integrating structural and metabolic data.

This paper develops a few-shot learning framework for cryo-EM micrograph classification using triplet loss embeddings, achieving competitive performance with minimal labeled examples.