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About

Amin Haeri is a researcher advancing the understanding of granular material behavior, with a primary focus on continuum modeling and its applications to machine-terrain interactions. His work is particularly impactful in the field of space exploration robotics, where he investigates how robot wheels interact with planetary regolith under reduced gravity conditions. Haeri’s major contributions include the development of a three-dimensional granular flow continuum model using the material point method with a hyperelastic nonlocal granular fluidity framework, which has garnered 38 citations and serves as a foundational tool for simulating complex granular dynamics. He has also pioneered the use of subspace graph networks for real-time granular flow simulation, integrating deep learning with continuum methods to enable efficient modeling of robot-terrain interactions. His research on gravity sensitivity in numerical solvers further highlights the critical role of gravitational effects in granular flow predictions. With a growing citation record and innovative approaches that bridge physics-based modeling and machine learning, Haeri’s work is shaping the future of autonomous mobility in extraterrestrial environments.