Anindita Nath’s work giving health data a voice—from building empathetic conversational agents for dementia caregivers to architecting genomic copilots and public health metadata platforms—is unified by a single design conviction: that the most consequential challenge in biomedical AI isn’t model accuracy, but minimizing the cognitive overload placed on the clinicians, researchers, and program managers who depend on these systems under pressure. Her career bridges the full stack of what that requires, from prosody modeling and natural language understanding to data architecture and responsible deployment, grounded in the belief that automation should make human expertise faster and more scalable—never a substitute for the judgment, ethics, and empathy that only humans can provide.