Muskan Chawla

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About

Muskan Chawla is a researcher at the intersection of artificial intelligence, robotics, and clinical communication science. Her primary research focuses on developing deep learning and robotic systems to detect and analyze emotional and pragmatic deficits in social communication disorders, such as autism spectrum disorder and social pragmatic communication disorder. Her most cited work, "Deep learning and robotics enabled approach for audio based emotional pragmatics deficits identification in social communication disorders" (2025), introduces a novel framework that integrates deep neural networks with a robotic platform to automatically identify audio-based emotional pragmatics impairments. This interdisciplinary approach bridges affective computing, human-robot interaction, and assistive technology, offering a scalable, objective tool for early screening and intervention. Although early in her career, her work has already garnered attention for its potential to transform diagnostic practices in clinical settings. By combining machine learning with embodied robotic agents, Chawla’s contributions promise to make social communication assessment more accessible, consistent, and data-driven, positioning her as an emerging voice in AI-assisted mental health and developmental disorder research.