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About

Asep Najmurrokhman is an Indonesian researcher whose work spans intelligent control systems, mobile robotics, and brain-computer interfaces. With a strong focus on applying artificial intelligence to real-world automation challenges, he has made meaningful contributions to the design and implementation of fuzzy logic controllers, neural networks, and signal processing techniques in robotic systems. His most-cited work (13 citations) pioneers the use of wavelet extraction combined with Recurrent Neural Networks for emotion-based Brain-Computer Interface control of robot simulators — a significant step toward intuitive human-machine interaction. Alongside this, Najmurrokhman has extensively advanced fuzzy logic control for mobile robots, developing Mamdani and Takagi-Sugeno-Kang type controllers for wheeled and hexapod robots to achieve reliable obstacle avoidance and motion efficiency, with individual works attracting up to 10 citations. His research portfolio further includes industrial manipulator arm design using color sensors and microcontrollers, PID-based auto-balancing robots, and image processing for soccer robots. Collectively, these contributions reflect a researcher committed to bridging theoretical intelligent systems with practical robotic implementations. Najmurrokhman's work offers valuable frameworks for students and engineers developing autonomous and adaptive robotic systems across manufacturing, industrial, and human-interface domains.