Jyoti Yadav is a first-year Ph.D. student at NYU specializing in the application of artificial intelligence to enhance mental health diagnostics. Her research focuses on utilizing large language models and speech signal processing to predict the severity of PTSD symptoms, aiming to develop non-invasive and accessible diagnostic tools.

Jyoti has developed advanced machine learning pipelines in the lab to extract and analyze digital biomarkers—such as speech transcriptions and acoustic signals—and correlate them with clinical disorders. Her previous contributions include pioneering multimodal data analysis techniques for tuberculosis detection using machine learning. She seamlessly blends innovative AI techniques with real-world healthcare challenges, especially in mental health assessment, and is committed to designing transparent, unbiased solutions that deliver meaningful clinical benefits.