Alessandro Palma

This paper introduces LabCompass, a generative inverse-modeling framework that optimizes culture conditions to steer human hematopoietic cell fate in vitro, demonstrating its effectiveness through iterative experimental validation.

The paper benchmarks gene expression reconstruction from single-cell latent representations, finding autoencoders perform best at low dimensionality and foundation models depend on decoder architecture.

scPortrait integrates single-cell images with proteomics and transcriptomics data to identify cancer-associated macrophage subpopulations and embed images into transcriptome atlases.

CellFlow predicts single-cell phenotypes from complex perturbations using flow matching, demonstrating accuracy in cytokine stimulation, drug treatments, and developmental modeling.

This paper introduces IMPA, a generative model that predicts cell morphological responses to chemical and genetic perturbations using untreated cell images as input, showing improved performance on structurally related compounds.