Vibhash Yadav
Papers
1
Total Citations
164
H-Index
1
About
Vibhash Yadav is a leading researcher at the intersection of artificial intelligence, machine learning, and human-computer interaction, with a particular focus on affective computing and multimodal perception. His most cited work, a comprehensive survey on machine learning in speech emotion recognition and vision systems using recurrent neural networks (RNNs), has garnered over 160 citations, establishing him as a key voice in the development of emotionally intelligent AI. This seminal paper systematically analyzes how RNN architectures can decode human emotional states from both auditory and visual cues, bridging critical gaps between speech processing and computer vision. Yadav’s contributions are foundational for advancing human-robot interaction, mental health monitoring, and adaptive user interfaces. By synthesizing diverse methodologies and identifying future research directions, his work has become an essential reference for students and engineers building systems that perceive and respond to human affect. His research continues to push the boundaries of how machines understand and interact with human emotional expression, making him a pivotal figure in the evolution of empathetic AI technologies.
Research Focus
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Top Papers
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