Dr. Feldman is an informatics researcher interested in the application of statistical, data mining and machine learning techniques to problems across the healthcare domain. With a focus on translational research, his work utilizes a heterogeneous array of clinical, operational and population-level data sources to better understand the data we collect, apply and analyze computational models, and ultimately evaluate and synthesize new knowledge around the practice and administration of healthcare

Working closely with multidisciplinary teams, Dr. Feldman’s work is deeply tied to the potential of informatics to understand variability within patient conditions and outcomes. Ultimately seeking to identify evidenced-based risk factors and treatment patterns that can be used to better inform the quality and effectiveness of care. Notably, embedded at the core of his work lies the notion of “augmentation, not automation”. Where he seeks to enhance the effectiveness of those engaged in the healthcare system, augmenting their existing skill sets rather than replacing the individual.