Amin Beheshti

Papers

Total Citations

126

H-Index

About

Amin Beheshti is a multidisciplinary researcher whose work sits at the intersection of artificial intelligence, cognitive computing, and business transformation. His research spans emotion recognition, technology adoption, and the strategic integration of AI-enabled technologies into real-world systems, making him a notable voice in both technical and applied AI communities. Beheshti's most influential contribution to date is his development of a Four-layer Convolutional Neural Network (ConvNet) for facial emotion recognition, which achieved strong performance with minimal training epochs while emphasizing the critical role of data diversity — a paper that has garnered over 100 citations since its 2022 publication. This work has clear implications for human-computer interaction, medical diagnostics, and human-robot communication. He has also made strides in understanding how humans adapt to emerging technologies, proposing a Cognitive Model for Technology Adoption (2023) that addresses the accelerating integration of AI, machine learning, and robotics across industries. As an editorial leader on business transformation through AI, Beheshti bridges the gap between technical innovation and organizational strategy. His growing citation record reflects a researcher whose interdisciplinary vision is increasingly recognized by both academic peers and industry practitioners.