Professor, Baylor College of Medicine
2 papers at NeurIPS 2025
Explicit clustering bias added during training improves structural consistency of cell embeddings but does not reveal clear cell types in mouse V1
TRACE is a contrastive learning framework that uses averaging of multi-trial neural activity to create interpretable 2D embeddings of large-scale neural recordings, revealing both continuous biological variation and discrete cell-type structures.
