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About

Dragan Kukolj is a researcher whose work spans robotics, wireless sensor networks, and business intelligence, with particular expertise in intelligent control systems and autonomous navigation. His most influential contribution lies in mobile robot navigation, where he pioneered the application of self-learning neural networks to guide real robotic platforms, later extending this framework by combining neural-fuzzy and neural network approaches to achieve more robust, collision-free movement — work that has collectively attracted his highest citation counts. Complementing this, Kukolj has made meaningful contributions to human-robot interaction, notably developing speaker localization techniques under echoic conditions to enable service robots to track and engage with users in real environments. His work on NITRO, a semi-autonomous remotely controlled robot with multimedia capabilities, demonstrated his interest in bridging theoretical control systems with practical telepresence applications. Beyond robotics, Kukolj contributed to wireless sensor network optimization and developed PSALM, a patent mining and business intelligence tool designed to extract competitive insights from large bibliographic and patent datasets. Though operating within a modest citation profile, his research reflects a consistent commitment to translating intelligent systems research into tangible, deployable technologies across multiple engineering domains.