Gabriel Paës

This paper develops a 3D U-net model for segmenting wood cells in confocal images to improve predictions of enzymatic hydrolysis efficiency.

The paper develops a hierarchical modeling framework to predict enzymatic saccharification dynamics by simplifying complex interactions through successive model reductions.

This study develops a pipeline to predict sugar conversion yields during plant cell wall enzymatic hydrolysis using autofluorescence and morphological changes, revealing strong negative correlations with conversion efficiency.

This study identifies a distinct autofluorescence pattern marking enzymatic deconstruction of plant cell walls and develops a computational pipeline to assess hydrolysis impact.

This study quantifies plant cell wall deconstruction at cell and tissue scales using imaging and computational tools, revealing correlations between compactness, neighboring cells, and cellulose conversion.