Muhammad Hafidz Ibnu Hajar

About

Muhammad Hafidz Ibnu Hajar is a researcher at the intersection of natural language processing and robotics, with a primary focus on sentiment classification and human-robot interaction. His most-cited work, "Sentiment classification of delta robot trajectory control using word embedding and convolutional neural network" (2022), introduces an innovative approach that bridges NLP and robotics by applying word embedding and CNN-based sentiment analysis to control delta robot trajectories. This pioneering contribution demonstrates how subjective information—such as opinions, emotions, and attitudes extracted from unstructured text—can directly influence robotic movement, advancing the field of intuitive human-robot collaboration. With 3 citations, this paper has laid groundwork for integrating emotional intelligence into robotic systems. His research addresses the challenge of classifying and recognizing subjective information from text to enable more responsive and adaptive robot behaviors. Hajar’s work is particularly notable for its interdisciplinary approach, merging deep learning techniques with practical robotic control, making it relevant for researchers in NLP, robotics, and human-computer interaction seeking to create more empathetic and context-aware machines.

Research Focus

Key Achievements

Top Papers

1. 1
   Sentiment classification of delta robot trajectory control using word embedding and convolutional neural network

   3 citations · 2022

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