Our informatics faculty members actively develop new methodology in artificial intelligence, natural-language processing and machine learning; these methods make possible novel analyses of clinical data from electronic-health records and from population-based studies of common diseases. Read about some of our findings.

Human health is a complex system influenced by the interplay among many demographic, environmental and genomic factors. Computational models of health must take this complexity into account. Read about our teaching approach that prepares student for such challenges.

Read the professional-life stories of our informatics faculty members. They are also affiliated with the Institute for Biomedical Informatics.

About Us

To understand health and disease today, we need new thinking and novel science —the kind  we create when multiple disciplines work together from the ground up. That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics. 

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