Papers
2
Total Citations
26
H-Index
2
About
N. Srinivasa is a leading researcher in computational neuroscience and neurorobotics, whose work bridges the gap between biological neural processing and autonomous robotic systems. His primary research areas include spiking neural networks, active vision, and self-organizing neural architectures for robot control. Srinivasa’s most significant contribution is his pioneering 2012 work on a self-organizing spiking neural model that learns fault-tolerant spatio-motor transformations, which has garnered 19 citations. This model integrates integrate-and-fire neurons with spike-timing-dependent plasticity (STDP) to enable robust learning of sensorimotor mappings, offering a biologically plausible framework for adaptive robot control. Earlier, in his 2002 paper, Srinivasa developed a neural network-based spatial representation for robot control with active vision, addressing calibration challenges in dynamic environments. This foundational work, with 7 citations, demonstrated how active camera systems could enhance robotic flexibility. Srinivasa’s research is notable for its emphasis on fault tolerance and self-organization, making his models highly relevant for real-world applications in autonomous systems. His work continues to inspire advances in neuromorphic computing and adaptive robotics, positioning him as a key figure in the intersection of neural computation and embodied intelligence.
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