Emma Lejeune

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About

Emma Lejeune is a rising leader in the intersection of mechanobiology, soft matter engineering, and computational mechanics. Her research focuses on how mechanical signals—from cellular forces to tissue-level deformations—can be programmed, measured, and understood in biological and engineered systems. In her highly cited 2023 work, *Mechanically programming anisotropy in engineered muscle with actuating extracellular matrices*, Lejeune demonstrated how hierarchical extracellular matrix design can direct muscle tissue alignment and function, offering a new paradigm for creating adaptive, living materials. This paper has already garnered 45 citations, reflecting its immediate impact on the field. More recently, in *Segmenting mechanically heterogeneous domains via unsupervised learning* (2024), she introduced a novel computational framework that uses machine learning to identify regions of distinct mechanical behavior in soft materials—a critical step for analyzing complex tissues and soft robots. Lejeune’s work uniquely bridges experimental mechanobiology and data-driven modeling, enabling researchers to both build and decode mechanical heterogeneity. Her contributions are shaping how we design adaptive biomaterials and analyze soft matter systems, making her a key voice in the future of mechanobiology and soft robotics.