Muhammad Saddam Khokhar
Papers
2
Total Citations
19
H-Index
2
About
Muhammad Saddam Khokhar is a researcher advancing the frontiers of artificial intelligence, robotics, and industrial automation. His work centers on developing sophisticated machine learning and deep learning frameworks to solve complex, real-world problems in perception, control, and data analysis. A key contribution is his pioneering approach to nonlinear dimensionality reduction for robot vision, where he introduced the Deep Three-Dimensional Spearman Correlation Analysis (D3D-SCA). This method, detailed in his most-cited paper (16 citations), significantly enhances the monitoring of industrial processes by extracting robust features from high-dimensional visual data. More recently, Khokhar has tackled the challenge of learning from complex, interconnected data structures. His 2025 work proposes a novel meta-reinforcement learning framework that synergistically combines Deep Q-Networks with Graph Convolutional Networks for effective graph cluster representation. This research is particularly impactful for the Internet of Things (IoT), enabling more intelligent and adaptive autonomous systems. By bridging the gap between advanced representation learning and practical robotic applications, Khokhar is shaping the next generation of intelligent, data-driven industrial and autonomous technologies.
Research Focus
Key Achievements
Top Papers
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