Sheifali Gupta
Papers
2
Total Citations
16
H-Index
2
About
Dr. Sheifali Gupta is a leading researcher at the intersection of artificial intelligence, industrial robotics, and medical image analysis. Her work is distinguished by pioneering AI-driven control strategies that enable robotic manipulators to learn and adapt autonomously in dynamic, unstructured industrial environments. Her most-cited paper, "AI-Driven Intelligent Control Strategies for Industrial Robotics: A Reinforcement Learning Approach" (2025), has already garnered 14 citations, signaling its transformative impact on the field. This research moves beyond conventional model-based controllers, introducing reinforcement learning frameworks that significantly enhance robotic performance and adaptability. Dr. Gupta also contributes to critical healthcare applications, as evidenced by her review on "Segmentation Techniques for Detection of Tuberculosis Using Deep Learning" (2023), which surveys computational methods for medical image analysis. Her work bridges the gap between theoretical AI advances and practical, high-impact solutions in both manufacturing and diagnostics. By integrating deep learning with real-world robotic and medical challenges, Dr. Gupta is shaping the future of intelligent automation and computer-aided diagnosis, making her a vital voice for students and researchers exploring the frontiers of applied AI.
Research Focus
Key Achievements
Top Papers
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