Asiful Arefeen

Bangladesh University of Engineering and Technology

Papers

Total Citations

H-Index

About

Asiful Arefeen is a researcher whose work sits at the intersection of artificial intelligence, affective computing, and cybersecurity. His most recognized contribution, "Convolutional Neural Network (CNN) Based Speech-Emotion Recognition" (2019), has garnered 69 citations and established a foundational approach for using deep learning to decode human emotional states from speech. This work is particularly significant for its dual focus: advancing human-computer interaction while also proposing practical applications in crime prevention and cyber threat detection. By demonstrating that speech—the most natural form of communication—can be systematically analyzed for emotional content, Arefeen has helped bridge the gap between raw acoustic signals and meaningful behavioral insights. His research holds promise for real-world deployment in security systems, mental health monitoring, and more empathetic AI interfaces. Arefeen’s contributions are especially valuable for students and researchers exploring the convergence of neural networks and affective computing, showing how technical innovation can address pressing societal challenges.