Aman Upaganlawar

Papers

Total Citations

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About

Aman Upaganlawar is a pioneering researcher at the intersection of artificial intelligence and neurodevelopmental disorders, with a primary focus on leveraging AI for the diagnosis and treatment of autism spectrum disorder (ASD). His most-cited work, "Leveraging AI for the diagnosis and treatment of autism spectrum disorder: Current trends and future prospects" (2024, 54 citations), provides a comprehensive synthesis of how machine learning, deep learning, and natural language processing are transforming early detection, behavioral analysis, and personalized intervention strategies for ASD. Upaganlawar’s contributions are notable for bridging the gap between cutting-edge computational methods and clinical practice, offering a roadmap for scalable, data-driven solutions that can improve outcomes for individuals on the spectrum. His research highlights the potential of AI to analyze complex behavioral patterns, speech anomalies, and neuroimaging data, enabling earlier and more accurate diagnoses. With 54 citations in a short span, his work has already garnered significant attention from both the AI and medical communities, underscoring its relevance and impact. Upaganlawar’s efforts are paving the way for more accessible, efficient, and equitable autism care, making him a rising voice in the field of AI-driven healthcare innovation.