Arshdeep Singh

Punjab Technical University, University of Agder

Papers

Total Citations

H-Index

About

Arshdeep Singh is a researcher at the forefront of affective computing and intelligent human-computer interaction, with a primary focus on facial emotion recognition and gesture-based interfaces. His most impactful work, a 2023 study on "Facial emotion recognition and music recommendation system using CNN-based deep learning techniques," has garnered 81 citations, establishing a foundational approach for integrating emotional AI with personalized content delivery. Singh’s contributions extend to edge computing, where he developed a vision transformer and lightweight CNN model for hand gesture recognition, achieving 13 citations for its efficient, real-time processing capabilities. His 2023 model for facial expression recognition with music recommendation further refines these techniques, demonstrating a consistent trajectory toward practical, user-centric applications. By bridging deep learning with real-world usability, Singh’s work has significant implications for assistive technologies, entertainment systems, and responsive environments. His research not only advances algorithmic accuracy but also prioritizes computational efficiency, making his models deployable on resource-constrained devices. For students and researchers, Singh’s portfolio exemplifies how targeted deep learning innovations can transform raw emotional data into actionable, empathetic systems.