Dr. Vacanti's research interests include combining high-throughput proteomics, metabolomics, and bioinformatic analyses with measurements of metabolic flux to identify pharmaceutical or dietary interventions to treat human disease. Dr. Vacanti's research group also builds, trains, and applies machine learning models that aid in predicting protein function in human disease.

Ongoing projects include:

1.) Identifying a metabolic etiology of Alzheimer's disease and understanding its intersection with insulin resistance.

2.) Creating a machine-learning-based approach to measure protein localization in a high-throughput manner.