Sonjoy Das

University at Buffalo, State University of New York

Papers

Total Citations

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About

Sonjoy Das is a leading researcher in uncertainty quantification and probabilistic modeling for complex engineering systems, with a particular focus on robotics and structural dynamics. His pioneering work introduces random matrix theory (RMT) as a powerful alternative to conventional parametric uncertainty models, which often fail when system parameter variation data is scarce. In his highly cited 2014 paper (8 citations), Das generalizes a random matrix-based uncertainty model from manipulator Jacobians to full dynamic models of robotic systems, offering a robust framework for capturing system fluctuations without requiring detailed parametric knowledge. His companion 2014 work (4 citations) further establishes the probabilistic formulation of the manipulator Jacobian using RMT, addressing the limitations of traditional random variable-based approaches. Das’s contributions are particularly impactful for complex robotic systems operating under uncertain conditions, where his methods provide more reliable predictions and safer designs. His research bridges theoretical advances in random matrix theory with practical engineering challenges, making his work essential reading for students and researchers in robotics, structural health monitoring, and uncertainty propagation.