Srikant Srinivasan
University of Saskatchewan, Rutgers, The State University of New Jersey
Papers
3
Total Citations
50
H-Index
3
About
Srikant Srinivasan’s research bridges two distinct worlds: the computational modeling of biological motor control and the mechanical performance of advanced composite materials. His pioneering work in the early 1990s introduced a movement pattern generator model using artificial neural networks (ANNs), a novel approach that applied neural network principles to motor control—a domain then dominated by studies of learning and association. This foundational paper, with 34 citations, laid early groundwork for bio-inspired robotics and neural motor control. Two decades later, Srinivasan shifted focus to experimental mechanics, investigating polymer matrix composite gears with varying fiber proportions. His 2020 study, cited 9 times, addresses the growing demand for lightweight, high-stiffness materials in industrial power transmission, offering practical insights into composite gear durability. He also contributed a novel ANN-based solution for maze traversal problems (2004, 7 citations), further demonstrating his versatility in applying neural networks to spatial navigation challenges. Srinivasan’s career exemplifies a rare interdisciplinary breadth—from neural modeling to materials engineering—making his work relevant to both computational neuroscience and mechanical design.
Research Focus
Key Achievements
Top Papers
- 1A movement pattern generator model using artificial neural networks34 citations · 1992
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