Tuan D. Pham

This paper introduces a tensor-derived similarity network framework to analyse spatial organisation in colorectal cancer and shows that spatial organisation constrains network structure.

This paper introduces RGAI, a geometric deep-learning framework for cross-domain analysis of spatial transcriptomics, enabling alignment of latent tissue states across diverse datasets.

This paper develops a spatial AI framework to identify conserved tissue-state organization across trauma, oral, and cardiovascular pathology using spatial transcriptomic data, finding six conserved fuzzy tissue states.

The paper investigates how odor information is routed through feedforward and feedback pathways in the mouse olfactory cortex, finding distinct temporal encoding and plasticity in neurons projecting to different targets.

This paper introduces a cross-domain spatial transcriptomic framework to analyze tissue repair dynamics, showing coherent tissue state separation and distinct spatial organization patterns in wound healing versus tumor microenvironments.

This paper uses phase portraits and fuzzy recurrence plots to analyze nonlinear dynamics in brain networks, showing they can capture functional connectivity and predict neural behavior.