Amit Kukker

Netaji Subhas University of Technology, Chandigarh University

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About

Dr. Amit Kukker is a pioneering researcher at the intersection of artificial intelligence, robotics, and biomedical engineering. His work centers on developing intelligent, adaptive algorithms that bridge reinforcement learning, fuzzy logic, and deep neural networks to solve complex control and classification problems. In his highly cited 2021 paper, "Stochastic Genetic Algorithm-Assisted Fuzzy Q-Learning for Robotic Manipulators" (19 citations), Dr. Kukker introduced a novel hybrid framework that optimizes robotic decision-making under uncertainty, significantly advancing autonomous manipulation. More recently, his 2024 work, "Biomedical Image Classification using Deep Reinforcement Learning," showcases his innovative fusion of deep learning’s representational power with reinforcement learning’s sequential decision-making. This amalgamated tool enables deep neural networks to learn from agent-environment interactions, achieving state-of-the-art accuracy in medical image analysis. By integrating stochastic optimization with fuzzy Q-learning, Dr. Kukker has created robust systems that excel in both industrial robotics and healthcare diagnostics. His contributions are shaping the next generation of AI-driven autonomous systems, demonstrating how hybrid intelligence can tackle real-world challenges from the factory floor to the clinic.