Dailin Marrero
Papers
2
Total Citations
37
H-Index
2
About
Dailin Marrero is a rising researcher at the intersection of robotics and computational neuroscience, whose work is pioneering more brain-like control systems for industrial automation. Her primary research areas include spiking neural networks (SNNs), neuromorphic control, and fuzzy logic systems for robotic manipulators. Marrero’s major contribution lies in demonstrating how SNNs, inspired by the human brain’s temporal coding mechanisms, can be applied to robotic controllers to achieve superior trajectory tracking accuracy and adaptability. Her most cited work, “A Novel Robotic Controller Using Neural Engineering Framework-Based Spiking Neural Networks” (2024), has already garnered 20 citations, signaling strong early impact in the neuromorphic engineering community. Complementing this, her 2023 study on fuzzy control strategies for a 3-DoF robotic arm—which developed both a Fuzzy Logic Controller and an alternative approach—has accumulated 17 citations and directly addresses the efficiency demands of Industry 4.0. By bridging biologically plausible neural computation with practical robotic control, Marrero is laying the groundwork for more energy-efficient, adaptive automation systems. Her work is particularly notable for its dual focus: advancing fundamental SNN theory while delivering tangible improvements in real-world robotic performance.
Research Focus
Key Achievements
Top Papers
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