Farrokh Sharifi
Papers
3
Total Citations
30
H-Index
3
About
Farrokh Sharifi’s research lies at the intersection of robotics, wireless communication, and neural computation, with a focus on enhancing the autonomy and reliability of systems operating in challenging, real-world environments. His early work on deploying WiFi repeaters for confined-space urban search and rescue (USAR) demonstrated a practical solution to a critical problem: extending wireless communication for first responders navigating hazardous, inaccessible disaster sites. This foundational contribution, cited 18 times, addresses a key bottleneck in emergency response technology. Sharifi later advanced the field of robotic perception through decentralized multi-camera fusion, developing methods for robust and accurate pose estimation in Cartesian space. This work, with 8 citations, is vital for applications ranging from object recognition to visual servoing, where precision and reliability are paramount. More recently, he has explored bio-inspired control, optimizing the parameters of spiking neural networks for mobile robot implementation. By employing reward-based spike-timing-dependent plasticity, his 2020 study (4 citations) enables non-holonomic robots to learn target attraction, bridging neuroscience and practical robotics. Sharifi’s career reflects a consistent drive to solve tangible engineering problems—from disaster response to autonomous navigation—using innovative, interdisciplinary approaches.
Research Focus
Key Achievements
Top Papers
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