Papers
2
Total Citations
7
H-Index
2
About
R Monisha is an emerging researcher at the intersection of neuromorphic computing and intelligent environmental robotics. Her primary research areas include spiking neural networks (SNNs) for robotic control systems and low-cost, machine learning-enhanced environmental monitoring platforms. Monisha’s most cited work, “Spiking Neural Networks for Robotic Applications” (2023, 4 citations), offers a foundational exploration of how biologically plausible SNNs—which mimic the nervous system’s electric spike generation—can advance robotic perception and decision-making beyond traditional artificial neural networks. Her second highly cited paper, “Arduino-Based Air Quality Monitoring Robot With ML Analysis” (2024, 3 citations), addresses critical public health concerns by developing an affordable, mobile system that detects hazardous gases linked to lung cancer, asthma, and heart disease. This work demonstrates her commitment to deploying practical AI solutions for real-world pollution challenges. Though early in her career, Monisha’s contributions bridge theoretical neuroscience-inspired computing with accessible, impactful engineering—a promising direction for sustainable robotics and environmental health technology.
Research Focus
Key Achievements
Top Papers
- 1Spiking Neural Networks for Robotic Applications4 citations · 2023
- 2Arduino-Based Air Quality Monitoring Robot With ML Analysis3 citations · 2024