Bambang Marhaenanto

Papers

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About

Bambang Marhaenanto is a researcher at the forefront of integrating artificial intelligence, the Internet of Things (IoT), and biomedical engineering. His primary research areas include brain-computer interfaces (BCI), deep learning for signal processing, and assistive robotics. His most cited work, "Artificial Intelligence IoT based EEG Application using Deep Learning for Movement Classification" (2021, 5 citations), addresses a critical challenge for individuals with hand amputations: translating brain signals into precise robotic control. By developing a system that classifies movement intentions from EEG signals using deep learning, Marhaenanto has contributed to making prosthetic arms more intuitive and responsive. This work bridges the gap between neural activity and machine actuation, offering a pathway to improved quality of life for those with limited motor activity. His research demonstrates a commitment to practical, human-centered AI applications, where cutting-edge machine learning meets real-world assistive technology. As a rising voice in the field, Marhaenanto’s work holds promise for advancing non-invasive neural control systems, with potential impacts on rehabilitation and human-robot interaction.