Hesheng Han

Papers

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About

Hesheng Han is a rising researcher in structural dynamics and computational mechanics, with a focus on the intersection of machine learning, multi-stable structures, and bio-inspired design. His work centers on developing innovative methods for modeling complex mechanical systems, particularly joint-assembled structures and origami-inspired deployable mechanisms. In his highly cited 2025 paper, "PINN-based joint identification and low-dimensional dynamical modeling of joint-assembled structures" (6 citations), Han pioneers the use of physics-informed neural networks to simultaneously identify joint properties and create reduced-order models, offering a powerful new tool for analyzing assembled structures with nonlinear interfaces. His complementary study, "Dynamics of flexible multi-stable origami with bio-inspired creases" (5 citations), explores how crease patterns inspired by natural systems can enable tunable multi-stability and dynamic behavior in flexible origami structures. Though early in his career, Han’s work already demonstrates significant impact, with his papers quickly gaining citations for their novel integration of data-driven techniques with classical structural dynamics. His research promises to advance the design of adaptive, reconfigurable mechanical systems for applications in aerospace, robotics, and smart structures.