Shaoxun Huang

Shaoxun Huang is a graduate student in mechanical engineering working to uncover the physical principles that govern multicellular organization and tissue morphogenesis. His research spans two core areas: modeling collective cell behavior using graph-based neural networks and exploring how cell-extracellular matrix (ECM) interactions drive emergent mechanical patterns. As a MathWorks Fellow, Shaoxun will develop computational frameworks to predict and design tissue dynamics, with applications in developmental biology, regenerative medicine, and programmable living materials. He uses MATLAB for high-throughput image processing, graph construction, mechanical modeling, and dynamic simulation. His custom pipelines integrate segmentation, machine learning, and batch computation to extract structural and topological features from microscopy datasets. He also simulates nonlinear force propagation through fibrous ECMs to explore how mechanical memory and spatial cues influence tissue deformation. Shaoxun’s work could advance our understanding of mechanobiology while enabling the engineering of reconfigurable tissues and bioinspired soft systems that adapt to their environment.