Subramaniam Ganesan
Oakland University, University of Rochester, University of Tehran
Papers
5
Total Citations
47
H-Index
3
About
Subramaniam Ganesan’s research career spans computer vision, robotics, and biomedical engineering, with a focus on developing intelligent systems for real-world applications. His most influential work, “A robust Hough transform technique for description of multiple line segments in an image” (2002, 32 citations), advanced image processing by improving line detection accuracy—a foundational contribution for autonomous navigation and industrial inspection. Ganesan also pioneered control strategies for multi-agent systems, as seen in “Server based control flocking for aerial-systems” (2014), which applies bio-inspired flocking algorithms to coordinate drone swarms. In biomedical engineering, he designed a “Sensory system device for suture-manipulation tension measurement for surgery” (2012), a sensor-based tool that prevents excessive force during suturing, directly enhancing patient safety. His work on “Genetic-based fuzzy model for inverse kinematics solution of robotic manipulators” (2002) further demonstrates his expertise in merging evolutionary algorithms with fuzzy logic for precise robotic control. Most recently, Ganesan is exploring AI-driven educational robots, with a 2025 pilot study on simulated socially assistive robots for early childhood learning. With a career spanning over two decades, his research consistently bridges theoretical algorithms and practical devices, impacting fields from manufacturing to medicine and education.
Research Focus
Key Achievements
Top Papers
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- 2Server based control flocking for aerial-systems7 citations · 2014
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