Ankur Singh

Papers

Total Citations

H-Index

About

Dr. Ankur Singh is a researcher at the forefront of cybersecurity and biometric authentication, with a particular focus on advancing face recognition technologies for real-world surveillance applications. His most cited work, "Surveillance Robots based on Pose Invariant Face Recognition Using SSIM and Spectral Clustering" (2018, 5 citations), addresses a critical challenge in modern security: the reliable identification of individuals regardless of head orientation or pose. Dr. Singh’s major contribution lies in integrating Structural Similarity Index (SSIM) with spectral clustering techniques to create a pose-invariant recognition system, enabling surveillance robots to accurately verify identities even under non-ideal conditions. This work bridges the gap between theoretical computer vision and practical robotics, offering a robust solution for authentication and authorization in dynamic environments. While his citation count is modest, the novelty of his approach—combining biometric precision with autonomous robotic platforms—highlights his innovative thinking in cybersecurity. Dr. Singh’s research is particularly valuable for students and engineers exploring the intersection of machine learning, robotics, and security, demonstrating how advanced algorithms can enhance real-time threat detection and access control.