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My research focuses on the clinical translation of artificial intelligence and machine learning methods to improve therapeutic response evaluation in neuromuscular disorders. I am Head of AI for Clinical Development in the Division of Neuromuscular Medicine, where we design and deploy AI-driven models that integrate multimodal data, including neuroimaging, electrophysiology, molecular and neurocognitive measures, and patient-reported outcomes, to quantify treatment effects and support individualized care.
In alignment with emerging genetic and disease-modifying therapies, our work emphasizes scalable and interpretable modeling approaches that learn from heterogeneous, multisite datasets. These models are designed to capture both shared and disease-specific patterns across neuromuscular conditions, enabling cross-disorder insights and practical deployment in clinical trials and real-world settings, with the goal of bringing advanced analytics closer to routine clinical and research workflows.
In alignment with emerging genetic and disease-modifying therapies, our work emphasizes scalable and interpretable modeling approaches that learn from heterogeneous, multisite datasets. These models are designed to capture both shared and disease-specific patterns across neuromuscular conditions, enabling cross-disorder insights and practical deployment in clinical trials and real-world settings, with the goal of bringing advanced analytics closer to routine clinical and research workflows.