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About

Dr. J. Surendiran is a versatile researcher whose work spans geospatial engineering, robotics, biomedical imaging, and remote healthcare technology. His most cited paper, "Digital Elevation Model and Terrain Mapping Using LiDAR" (2021, 41 citations), establishes his foundational contributions to precise topographic modeling and environmental sensing. In robotics, Dr. Surendiran developed a machine learning framework that enables robots to autonomously fine-tune their parameters using pendulum-based self-adjustment principles, a novel approach for maintaining mechanical systems at peak performance (2022, 23 citations). His impactful work in medical imaging includes an unsupervised machine learning method for detecting glaucoma by analyzing the cup-to-disc ratio from fundus images (2022, 16 citations), offering a scalable screening solution for early diagnosis. Additionally, he designed a "Virtual Doctor" teleconsultation system using Arduino UNO and Node MCU that monitors heart rate, temperature, and SpO2 while incorporating UVC sterilization (2022, 7 citations), addressing critical needs in remote patient care. With over 87 citations across his key publications, Dr. Surendiran demonstrates a remarkable ability to apply computational intelligence across diverse domains, from autonomous systems to public health, making him a notable contributor to interdisciplinary engineering research.