The Syed Lab uses cutting-edge molecular and data scene techniques to study intestinal structure and function in patients with lumenal inflammatory enteropathies such as Crohn’s disease, ulcerative colitis, celiac disease, and environmental enteropathy (a primary driver for stunting in low-to-middle income countries. We believe that integrating artificial intelligence and machine learning with modern biomedical research has the potential to transform both our scientific understanding and clinical management of the most pressing global health concerns. In our work, we aim to improve global health and combat childhood undernutrition through enhanced diagnostics, accurate predictions of disease outcomes, and discovery of novel treatment strategies. By leveraging the power of data science to transform clinical care and facilitate precision medicine, we strive to ensure all children around the world live happy, healthy lives.

Our primary goals are to:

• Computationally explore key features of lumenal inflammatory enteropathies such as celiac disease, environmental enteropathy, and Crohn’s disease to predict patient-specific outcomes of disease.
• Identify metabolic signatures of luminal inflammatory enteropathies which can inform subtype predictions, reveal biomarkers of disease, and illuminate new therapeutic targets.
• Map the early childhood gut at single-cell resolution with linked contextual data on tissue morphology, ancestry, geography, and environment.

Our current areas of research are:

• Global childhood health and undernutrition
• Luminal inflammatory enteropathies
• Data science-driven precision medicine technologies