Research Projects

Understanding how biological materials organize into specific geometries is a growing area of interest in engineering research. Enclosed volumes with arbitrarily curved surfaces are a common feature across various levels of biological organization, such as in developing embryos and organs like the heart. In natural systems, cells form tissues through a mix of processes, including cellular signaling, intercellular adhesion, collective migration, cytoskeletal contractility, and environmental interactions. Advances in microscopy, genetic engineering, biochemistry, and computational modeling over recent decades have provided a more quantitative understanding of these processes. This project leverages these insights to design tissues that can self-organize into specific shapes driven by mechanical patterns originating from chemical patterns produced by gene regulatory networks. Our goal is to build a computational framework that models chemical pattern formation specifically on curved surfaces using reaction networks, along with the resulting surface deformations caused by these patterns. Using this framework, we plan to formulate a set of forward and inverse problems. For example, what patterns of mechanical property are needed to shape a tissue surface into a specific form? what minimal set of positional cues (chemical patterns) and gene regulatory networks can create the desired pattern on a tissue surface? Overall, this project aims to develop a computational framework to predict the essential components for closed curved tissues to self-organize into target geometries, guiding the practical implementations through genetic engineering and 3D bioprinting.