Anju Yadav

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About

Anju Yadav is a researcher at the forefront of affective computing and intelligent systems, with a primary focus on emotion recognition, machine learning, and their applications in healthcare and social networks. Her most cited work, "Emotion Recognition With Facial Expression Using Machine Learning for Social Network and Healthcare" (2020), has garnered 4 citations and stands as a foundational contribution to the field. In this study, Yadav systematically applied machine learning techniques to facial expression recognition (FER), enabling the classification of seven core emotional states—disgust, joy, surprise, anger, sadness, contempt, and fear—based on FER describing coefficients. Her work highlights the practical significance of FER across diverse domains, including robotics, social media analytics, and patient monitoring in healthcare. By bridging computational models with real-world emotional intelligence, Yadav’s research advances human-computer interaction and offers scalable tools for mental health assessment. Her contributions are particularly notable for integrating robust feature extraction with accessible machine learning frameworks, making emotion-aware technology more viable for non-specialist applications. As the demand for empathetic AI grows, Yadav’s insights continue to inform both academic inquiry and practical system design.