Moses C. Nah
Moses C. Nah is a PhD candidate whose research interests lie at the intersection of robotics engineering and motor neuroscience. Specifically, Moses seeks to understand how humans achieve dexterity far superior to modern robots and apply this understanding to bridge the gap between human and robot performance. Through close consideration of the ways in which humans manipulate infinite-dimensional objects with complex dynamics (e.g., a bullwhip), he is testing the hypothesis that humans achieve their remarkable dexterity by using a limited “library” of highly stereotyped actions. Using optimization and computer simulation of several models, Moses has shown that a single such movement was sufficient to achieve accurate target acquisition. MathWorks has been a fundamental tool in Moses’s work, and he is a co-developer of Explicit, an open-source MATLAB-based robotics software, which implements robot kinematic and dynamic equations based on the product-of-exponentials formulation with remarkable computational speed.
A MathWorks Fellowship will enable Moses to expand this successful body of work, which has the potential to help solve challenges in soft robot control and advance research and technology development in robotics at large.