Khurshid Aliev
Papers
18
Total Citations
243
H-Index
8
About
Khurshid Aliev is a researcher specializing in human-robot collaboration (HRC), industrial robotics, and intelligent automation within the frameworks of Industry 4.0 and 5.0. His work sits at a compelling intersection of human factors, machine learning, and collaborative robotics, addressing both the technical and ergonomic challenges of deploying robots alongside human workers in modern manufacturing environments. Aliev's most influential contribution, "User Experience and Physiological Response in Human-Robot Collaboration" (2022, 72 citations), broke new ground by examining the psychological and physiological effects of working alongside industrial robots — a critical concern as human-centered manufacturing gains prominence. His complementary research on machine learning-based robot monitoring systems (2021, 39 citations) advances predictive maintenance and safety compliance in collaborative workcells, directly tackling reliability challenges under demanding industry safety standards. Beyond human factors, Aliev has made notable advances in task-based robot programming, assembly sequence generation using reinforcement learning, fuzzy inference for task classification, and energy-efficient path planning for autonomous mobile robots and cobots. His work on interpretable fault diagnosis using fuzzy cognitive maps (2024) further demonstrates his commitment to transparent, intelligent industrial systems. With over 200 cumulative citations, Aliev's research meaningfully shapes the future of safe, efficient, and human-centric robotic collaboration in smart factories.
Research Focus
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