NICHOLAS P. TATONETTI is Herbert Irving Assistant Professor of Biomedical Informatics at Columbia University with interdisciplinary appointments in the Department of Systems Biology and the Department of Medicine. He received a Ph.D. in Biomedical Informatics from Stanford University in 2012, and dual B.S. degrees from Arizona State University in computational mathematics and molecular biosciences/biotechnology. Dr. Tatonetti researches the use of observational clinical data and high-throughput molecular data to identify and explain the pharmacological effects of drugs and drug combinations. He develops large-scale statistical and data mining techniques to address issues of bias and confounding in large observational datasets.

Dr. Tatonetti is an Irving Scholar, a Kavli Fellow, and the recipient of an Early Investigator Awards from the American Medical Informatics Association and the PhRMA Foundation. His work received Best Paper and Presentation awards at the AMIA Summit on Translational Bioinformatics (2010, 2011, 2015) and his work has been featured in the IMIA Yearbook of Medical Informatics in 2012. Dr. Tatonetti was profiled by Genome Web in their 2012 Young Investigator Profiles and as the Face of AMIA in 2016. He is author on over 80 peer-reviewed scientific publications and his work has been featured by The New York Times, The Chicago Tribune, The Boston Globe, Science Careers, among others.


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Dr. Nicholas Tatonetti is assistant professor of biomedical informatics in the Departments of Biomedical Informatics, Systems Biology, and Medicine and is Director of Clinical Informatics at the Herbert Irving Comprehensive Cancer Center at Columbia University. He received his PhD from Stanford University where he focused on the development of novel statistical and computational methods for observational data mining. He applied these methods to drug safety surveillance where he discovered and validated new drug effects and interactions. His lab at Columbia is focused on expanding upon his previous work in detecting, explaining, and validating drug effects and drug interactions from large-scale observational data. Widely published in both clinical and bioinformatics, Dr. Tatonetti is passionate about the integration of hospital data (stored in the electronic health records) and high-dimensional biological data (captured using next-generation sequencing, high-throughput screening, and other "omics" technologies). Dr. Tatonetti has been featured by the New York Times, Genome Web, and Science Careers. His work has been picked up by the mainstream and scientific media and generated thousands of news articles.